Best practices text segmentation

Best practices for text segmentation in translation include using Computer-Assisted Translation (CAT) tools to break text into meaningful, logical units like sentences or phrases, ensuring segments are concise and retain complete units of meaning to fit short-term memory, and prioritizing consistency through defined rules and Translation Memories (TMs) to improve quality and efficiency. Additionally, proper source document formatting, including clear structure and avoiding unnecessary formatting, helps CAT tools parse content correctly and create clearer segments. 

Understanding Text Segmentation

• Definition: Text segmentation is the process of dividing a source text into smaller, translatable units, called "segments". 

Best Practices for Text Segmentation

1. Break into meaningful units: Segment text at natural linguistic boundaries, such as sentences, rather than arbitrary points like every 5-10 words.
2. Keep segments concise: Segments should be short enough for a translator to easily retain the information in their short-term memory.
3. Ensure completeness: Each segment should represent a complete thought or unit of meaning to avoid confusion and an unnatural translation.
4. Utilize CAT Tools & Translation Memories: CAT tools, when configured with appropriate segmentation rules, help identify and manage these units. This promotes consistency and allows for the reuse of previously translated segments in a Translation Memory.
5. Format source content well: Clear, well-organized source documents with consistent formatting (e.g., proper use of paragraph breaks, hard returns, and page breaks) ensure that CAT tools can parse the content correctly and produce unambiguous segments.
6. Define segmentation rules: Establish clear rules, often in a format like SRX (Segmentation Rules Exchange), to define how text should be broken down for specific projects or language pairs.
7. Perform automated QA checks: After segmentation and translation, automated quality assurance checks help identify and correct errors like misspellings or incorrect terminology, preventing them from being added to the Translation Memory.
8. Prioritize consistency: Over time, consistent segmentation practices, combined with well-maintained TMs, significantly increase content reuse, reduce translation costs, and boost overall translation quality. 

• Purpose: It makes translation faster, easier, and more consistent by allowing translators to focus on smaller, logical chunks of text. 
• Tools: Segmentation is a foundational step in Computer-Assisted Translation (CAT) tools and is configured using specific segmentation rules. 

Best strategy? for AI inter-linea display

 The best strategy for producing an interlinear display of a translation using Google Translate is to translate the complete submission first and then use client-side logic (JavaScript/CSS) for display conversion.

---

Analysis of Strategies

1. Translate Complete Submission First (Recommended)

   • Process: Send the full sentence or segment to the Google Cloud Translation API. The API uses Neural Machine Translation (NMT), which translates the entire sentence at once to ensure contextual accuracy and capture nuances, idiomatic expressions, and complex grammar.¹ The complete translated text is returned. Client-side code (JS/CSS) is then used to align the original text with the translated text for an interlinear (line-by-line or word-under-word) display, often by segmenting the text into smaller chunks (e.g., words, phrases) and attempting to map them, or simply displaying the source text and the full translation on separate lines.

   • Pros:

     • Highest Quality Translation: NMT produces the most human-like and contextually accurate result.²

     • Efficiency: Fewer API calls are made (one per sentence/segment), which is generally faster and more cost-effective.

   • Cons:

     • Alignment Challenge: The primary difficulty is that Google's NMT does not provide a direct word-to-word or phrase-to-phrase mapping in its standard API response. Perfect alignment for an interlinear display is often an extremely complex, if not impossible, computational challenge without the underlying translation model data.

2. Translate Words and Phrases Iteratively (Not Recommended)

   • Process: Break the source text down into individual words or small phrases and make a separate API call for each one. Then, display the original word and its corresponding translation.

   • Pros:

     • Simple Alignment: Alignment is trivial since each call corresponds to a single word/phrase.

   • Cons:

     • Poor Translation Quality: Google's NMT is specifically designed to work on full sentences to understand context.³ Translating isolated words or short phrases loses context, resulting in poor, literal, and often incorrect translations.⁴

     • Inefficiency & Cost: This dramatically increases the number of API calls, leading to higher latency and significantly greater costs.

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Conclusion

Since Google Translate's core strength is its contextual Neural Machine Translation, you should prioritize translation quality by sending the full segment. The trade-off is that you will need to implement a sophisticated (and likely imperfect) client-side logic to attempt to align the words for the interlinear display.

The other strategy involves losing the key benefit of Google Translate's technology.

To see how to get started with the Google Translate API, watch ... video: How to use the Google API to translate texts. This video is relevant because it demonstrates using the Google Translate API, which is the necessary first step for either strategy.

Environment and AI solutions

 

20.09.25, ref. per Gemini

Question. Which is more friendly to the environment, for example in terms of electricity usage, carbon footprint, etc., client-side or server-side AI solutions? 

Response. In general, client-side AI solutions are more environmentally friendly than server-side solutions, but the answer is complex and depends on many factors. Client-side solutions, which run on a user's local device, eliminate or reduce the need for massive, energy-intensive data centers for inference (the use of a trained AI model). However, the training of these models, regardless of where they are ultimately deployed, remains a major environmental concern.

***

### Server-Side AI: The Environmental Burden

Server-side AI relies on large-scale data centers, which are one of the biggest contributors to the environmental footprint of AI. These data centers consume immense amounts of electricity for three main purposes:

* **Training and Inference:** The process of training a large language model (LLM) like GPT-4 can consume a staggering amount of energy. While a single query (inference) uses a tiny fraction of that energy, the sheer volume of billions of daily queries for popular models adds up to a massive cumulative carbon footprint.
* **Cooling:** Data centers generate a tremendous amount of heat. To prevent hardware from overheating, they require sophisticated and highly energy-intensive cooling systems, which can also consume millions of gallons of water annually.
* **Idle Capacity:** To ensure high availability and responsiveness, data centers must maintain a degree of idle capacity, which still consumes energy while waiting to handle traffic spikes.

The carbon footprint of server-side AI also depends on the **location** of the data center and its energy source. A data center running on a grid powered by renewable energy like wind or solar will have a significantly lower carbon footprint than one relying on fossil fuels.

### Client-Side AI: The Greener Alternative

Client-side, or on-device, AI runs directly on a user's device, such as a smartphone or laptop. Because the processing happens locally, it avoids the energy consumption and carbon emissions associated with data transmission and large data centers.

While client-side AI is more efficient for **inference**, it's crucial to understand a few key points:

* **Training is still a major factor:** The initial training of the AI model, whether it's for on-device or server-side use, is the most energy-intensive part of the process. This training is almost always done in a data center.
* **Limited Capabilities:** On-device models are typically smaller and less powerful than their server-side counterparts. This is because consumer devices lack the massive computational power and memory of a data center.
* **Device-level Consumption:** While they bypass the data center, on-device models still use a device's battery and CPU, which consumes energy. This can lead to faster battery drain and generate some heat.

### A Nuanced Comparison

Ultimately, the choice between client-side and server-side AI for a given application is a trade-off between performance and environmental impact. For computationally demanding tasks like training a large generative AI model, a server-side solution is currently the only option. For tasks that can be performed by smaller models, such as basic text completion or image classification, client-side AI is a much more energy-efficient and environmentally responsible choice.

As on-device hardware becomes more powerful and AI models are optimized to be smaller and more efficient, we'll likely see a shift toward more client-side solutions, reducing the reliance on energy-hungry data centers for many everyday AI applications.

Some interesting links

 [This post is open-ended. As links become known and are assessed relevant to the discussions here, they will be added. Got something to suggest?] 

https://eurolinguiste.com/interlinear-books-review-a-dual-language-book/

https://interlinearbooks.com/

https://www.alexanderarguelles.com/academy/

https://textanalysisonline.com/nltk-sentence-segmentation 

And here are some more with short notes.

https://readlang.com/
nifty online teaching/learning using interlinear concepts and web page technologies

https://interlinearbooks.com/tools/interlinearizer/
multi-step process on- and off-line, labor intensive

https://paratext.org
multi-step process within a software program using training corpora

https://github.com/gbroques/interlinearizer/blob/main/README.md
may be useful in building interlinear, aligned translations

https://www.lucalampariello.com/create-interlinear-texts/
Imtranslator enthusiast, recommended

https://interlinearbooks.com/tools/interlinearizer/splitter/
text splitter, useful

https://github.com/lukastk/interlinearize
relies on Calibre conversions, looks promising as local/server-side solution for longer works 

Hyrskykari, Aulikki & Majaranta, Päivi & Räihä, Kari-Jouko. (2005). From gaze control to attentive interfaces. Interactive applications that make use of eye tracking have traditionally been based on command-and-control. Applications that make more subtle use of eye gaze have recently become increasingly popular in the domain of attentive interfaces that adapt their behaviour based on the visual attention of the user. We provide a review of the main systems and application domains where this genre of interfaces has been used.

OpenAI API key

[Check the OpenAI website for the latest . . . this is an old post.]

Here's a step-by-step guide to obtain an OpenAI API key and considerations for using it in a web application:

---

### **Steps to Get an OpenAI API Key**

#### **1. Create an OpenAI Account**
1. Go to [OpenAI's website](https://openai.com/).
2. Click **Sign Up** to create an account, or **Log In** if you already have one.

#### **2. Access the API Section**
1. Once logged in, navigate to the OpenAI **API Dashboard** at [https://platform.openai.com/](https://platform.openai.com/).
2. Click on your profile picture in the top-right corner and select **API Keys** from the dropdown menu.

#### **3. Generate an API Key**
1. On the API Keys page, click the **Create new secret key** button.
2. A new API key will be generated. Copy the key immediately, as it will only be displayed once.
   - Save the key securely (e.g., in a password manager).

#### **4. Set Up Billing**
1. Go to the **Billing** section in your account settings.
2. Add a valid payment method to enable API usage.
   - Note: OpenAI offers a free trial for new users with a limited amount of credits. Check the specific details on their pricing page.

---

### **Considerations for Using the API Key**

#### **1. **Costs**
- **Pay-as-you-go model**: You will be charged based on usage.
- Refer to OpenAI’s [pricing page](https://openai.com/pricing) to understand the costs per token for different models (e.g., GPT-4, GPT-3.5).
- Monitor usage carefully to avoid unexpected charges by setting usage limits in the **Usage** section of your dashboard.

#### **2. **Rate Limits**
- OpenAI imposes rate limits on API usage. Check your account for specific limits and adjust your use accordingly.

#### **3. **Compliance**
- Review OpenAI's **Usage Policies** to ensure you comply with their guidelines, particularly when dealing with translations that may involve sensitive or copyrighted content.

---

### **Implementation in the Web App**

Users input their API key to perform translation requests. In doing so:

1. **Input Field for API Key**
   - You have a secure input field where you can enter your API key.
   - User's API keys are not saved on the server.

2. **Translation Request**
   -Translations and displays are not guaranteed one hundred percent accurate. 
   -Proofread results. Report any problems . . . so we (OpenAI and the web app provider) can improve.

Word/char count?

For reference--English

Based on the average word length of 5 to 6 characters (including spaces and punctuation), 300,000 characters is approximately 50,000 to 60,000 words.

Proofreading, copyediting, etc.*

[In reference to a another post here having to do with  reduction in demand for people-type translators . . . these people/roles below are still needed. AI and automation can't perform this work, yet. I don't think developing technologies will any time soon if ever.]

Copywriting and proofreading are two distinct activities in the realm of writing and editing. Here's an overview of their differences.

Copywriting

Copywriting refers to the process of crafting written content, typically for advertising or promotional purposes. The primary goal of copywriting is to engage the audience, persuade them, and drive them to take a specific action. Copywriters create content for various mediums such as advertisements, websites, brochures, social media campaigns, and more. They focus on conveying a compelling message, highlighting the benefits of a product or service, and employing persuasive techniques to capture attention and elicit desired responses. Copywriters often work closely with marketing teams to align their writing with the overall brand strategy and target audience.

Proofreading

Proofreading, on the other hand, involves reviewing and correcting written material to identify errors and ensure accuracy, consistency, and clarity. Proofreaders examine text for grammatical mistakes, spelling errors, punctuation issues, and typographical errors. They also check for proper formatting, adherence to style guidelines, and overall readability. Proofreading is typically done after the writing phase to polish the content and make it error-free. Proofreaders have a keen eye for detail and possess strong language skills, enabling them to spot errors that might have been overlooked during the writing process. 

In summary, copywriting focuses on creating persuasive and engaging content for marketing and promotional purposes, while proofreading concentrates on reviewing and correcting written material to eliminate errors and enhance readability. Both copywriting and proofreading play essential roles in producing high-quality written content.

---

What is the difference between a copyeditor and editor?

The terms "copyeditor" and "editor" are often used interchangeably, but there are subtle differences between the two roles. Here's an explanation of their distinctions.

Copyeditor

A copyeditor is responsible for reviewing written material, such as articles, manuscripts, or documents, with a focus on improving the overall quality, accuracy, and consistency of the text. Copyeditors meticulously examine the content line by line and make corrections or revisions to ensure clarity, coherence, and adherence to grammar and style guidelines. They pay attention to grammar, spelling, punctuation, syntax, and usage errors. Additionally, copyeditors may suggest improvements in sentence structure, word choice, and overall readability. They work closely with the author to maintain the author's voice and intent while enhancing the presentation of the material.

Editor

An editor, in a broader sense, can encompass various roles and responsibilities depending on the context. Editors can be involved in different stages of the writing process, including content development, structural editing, copyediting, and proofreading. They often oversee the entire editing process and collaborate with writers to shape the content In essence, a copyeditor primarily focuses on improving the technical aspects of the written material, such as grammar and style, while an editor encompasses a broader role, often involved in guiding and shaping the content's structure, organization, and overall impact. 

However, it's important to note that the specific roles and responsibilities can vary across different contexts and publications.and ensure its effectiveness. Editors may provide feedback on the overall structure, organization, and flow of the material. They may also address issues related to tone, audience engagement, and narrative consistency. Editors have a comprehensive understanding of the target audience and the publishing industry and may contribute to decision-making regarding content selection and overall direction.

In essence, a copyeditor primarily focuses on improving the technical aspects of the written material, such as grammar and style, while an editor encompasses a broader role, often involved in guiding and shaping the content's structure, organization, and overall impact. However, it's important to note that the specific roles and responsibilities can vary across different contexts and publications.

Language learning and translation displays

QUESTION. Is there research about language learning using translations displayed
or printed in different ways, for example side by side versus in interlinear fashion?*

RESPONSE: [T]here has been research into the effectiveness of different translation
display formats, such as side-by-side (parallel text) and interlinear text, for language
learning. These studies generally focus on how the arrangement of translations can
impact comprehension, retention, and the learner’s ability to acquire new vocabulary
and grammar structures. Here’s a brief overview of findings related to these formats:
### 1. **Parallel (Side-by-Side) Texts**
- **Advantages**:
- Allows the learner to compare the original language and translation easily.
- Enhances understanding of structure, as learners can see how ideas are expressed
differently across languages.
- Encourages active engagement as the learner switches between languages to
decipher meaning.
- **Disadvantages**:
- Can cause learners to rely heavily on the translation, reducing the need to
struggle with the original language.
- Switching focus between two columns can slow down reading fluency and
comprehension in the target language.
**Research Findings**:
- Learners often benefit from side-by-side texts when they are at a beginner or
intermediate level, as it facilitates understanding and reduces cognitive load.
- A 2017 study showed that parallel texts help learners notice differences in
sentence structures and word usage, improving grammatical understanding.
### 2. **Interlinear Texts (Word-for-Word Translation Below the Original)**
- **Advantages**:
- Gives a word-by-word or phrase-by-phrase translation, which can help learners
focus more on sentence construction and vocabulary acquisition.
- Learners do not need to switch between two columns, allowing for smoother
reading of the original text.
- **Disadvantages**:
- May interfere with comprehension since the translations are more literal, which
can make understanding the natural flow of the target language difficult.
- Learners may become dependent on the direct translations rather than processing
the meaning holistically.
**Research Findings**:- Interlinear texts are more effective for acquiring vocabulary, especially for
learners at an early stage, because they expose them to the structure and syntax of the
target language.
- A 2019 study indicated that learners using interlinear texts often focus more on
individual word meanings and syntax, which can slow down comprehension but
deepen understanding of linguistic patterns.
### 3. **Cognitive Load and Efficiency**
- Research into *cognitive load theory* in language learning has found that how
translations are displayed can affect how much mental effort is required to learn new
material.
- Studies suggest that interlinear texts can reduce cognitive load for beginner
learners, but parallel texts are often more useful as learners advance and need to focus
on broader context and meaning.
### 4. **Mixed Methods (e.g., Bilingual Reading with Occasional Interlinear
Assistance)**
- Some studies propose using a hybrid approach, where learners use parallel texts
for general comprehension and interlinear texts for detailed vocabulary or grammar
studies.
- A 2021 research paper indicated that switching between these formats can be
especially effective for learners who struggle with comprehension but are ready to
move beyond beginner vocabulary.
In summary, both side-by-side and interlinear formats have their strengths depending
on the learner’s level and the goals of the language learning task. Interlinear texts are
often better for detailed linguistic study and vocabulary building, while side-by-side
texts are helpful for general comprehension and sentence structure comparison.
__________
* https://chatgpt.com/share/67160e03-5980-8009-b225-48bdba63de25
generated 21.10.2024 (link may not be available as of this post)

EN >> EN

One objection to interlinear translations is that it encourages other-language learners to translate when trying to use/learn the target language, to wit, best to think in the target language, not your native tongue. What to do? not use interlinear translations as one of your tools to comprehend/acquire the foreign language?

I think not, with an exception or two.

No one (of the rest of us) suggests reading whole books that have been translated and displayed in interlinear form. At least no language teacher should promote this. [objection coming soon] The object of learning is to take what you don't know perfectly and work with it until you do. This translates into bite-sized bits, or bytes if you prefer.

Which suggests offering what I and others more proficient than I do, provide language-learner friendly EN-to-EN translations. This is not interlinear but the intermediary step between being lost or almost lost in the target language to seeing in simpler target language what was lost/almost lost when grappling with an unfamiliar passage or short document presented in that target language, English here being only an example.

How can this transition be accomplished? Here is one way.

Have English practice conversations online for intermediate and above conversation partners. In process, correct, clarify, and expand or enhance the language that is or can be used with whatever topic is being discussed. Note these words, phrases, expressions, and potential uses of the language used or encountered. After the conversation has ended, take those notes, clean them up, perhaps augment with examples, and offer them to your conversation partners. Here is what that might look like in an email message as follow-up to an online conversation.

tooth pulled/extracted = removed from his/her mouth by surgeon or dentist or in your dog's case, the vet
pendant = a charm or jewel on a chain or cord worn around the neck
cremate = burn a dead body
urn = where the ashes of the cremated body are kept, sometimes
camping stove = portable gas stove
backpacking = to go overnight in the mountains or somewhere with a backpack . . . you carry everything you need, including water, food and chocolate
picnic = to eat outside somewhere other than your backyard, something special not just grabbing a sandwich and eating it on the park bench

If you are providing such online conversation practice sessions long term with a partner, about Christmas or another time make an e-book of all the notes and send it as a gift or resource. The recipient can use the book for study and review, or even search the book after conversations have long since ended. Here is an example in e-book format.

Chat notes epub example

You were waiting for the exceptions, weren't you? 

Well, one is a case I am very familiar with. In struggling with Latin for six years, I used interlinear translations that my father bought for me at the University of California bookstore. These were, for example, the speeches of Cicero. Given an assignment by my Latin teacher, I would look up the speech and use the interlinear translation to help me work up something I flipped as my own translation and handed it in. Survival but not thrival, you might say.

I don't know anyone, but there is at least one, who can think in Latin, or speak it. [https://www.alexanderarguelles.com/academy/ includes a circle on speaking Latin]] In other words, the goal of learning Latin for most of us is not to think in the language nor speak it. Interlinear translations, even of longer works, works that is that have practical value in helping to decode what was said long ago.

An aside having to do with a younger, er less mature, me. I took the interlinear Latin translations and tried to come up with my way of saying the same thing as the English lines provided. I could not produce my own, better English to English other than what appeared in the interlinear book. I was too inexperienced in my own language to do same. What are the implications of this for the EN-to-EN language learner? If the translation to easier to understand language is not very good, well that's a problem, if we assume we have a basic understanding of the target language. Hopefully for my students and conversation partners today, I am better at this "translation" skill. They will judge, after all I have had almost a lifetime to work on my abilities.  But I never know without direct feedback, which I get if I ask.

The next exception is that there are some, for example biblical scholars, translators, and linguists, who want the full monty, interlinear translations and glosses of important or critical texts that have ramifications beyond the scholar's personal understanding and gratification. Longer interlinear translation displays have a place, but for the rest of us? not so much in my opinion.

Intro--further study

The following is from a question posed to https://www.perplexity.ai/ on 27.11.24.

---

Research on reading interlinear text, where the source language is presented on one line and the target language on the next, has gained attention, particularly in relation to eye movement studies. Here are some key findings and methodologies from recent studies:

## Eye Movement Studies in Reading

**1. Eye Tracking as a Tool**  
Eye tracking is widely used to investigate how readers process text. It captures detailed information about eye movements—fixations (where the eyes stop) and saccades (rapid movements between fixations)—which are crucial for understanding cognitive processes during reading. Studies have shown that reading involves a complex interplay of visual attention and cognitive processing, with readers often skipping words or returning to previous ones based on context and familiarity with the material[1][4].

**2. Interlinear Text and Cognitive Processing**  
While specific studies on interlinear text are limited, related research indicates that the format can significantly impact reading efficiency. For example, a study explored how different line spacing affected reading in Chinese, revealing that eye movement patterns can be influenced by text presentation styles[1]. This suggests that interlinear formats might similarly affect how readers allocate their visual attention.

**3. Effects of Text Manipulation**  
Studies examining mirrored text (both vertically and horizontally) provide insights into how alterations in text presentation can disrupt reading processes. These investigations found that such manipulations increased reading times and altered fixation patterns, indicating that cognitive load increases when readers encounter unexpected formats[2]. This could imply that interlinear text may also require additional cognitive resources, potentially affecting comprehension and speed.

**4. Implications for Language Learning**  
The use of interlinear text has implications for language learning, as it may facilitate understanding by allowing learners to see direct translations alongside original text. However, the effectiveness may depend on factors like the reader's familiarity with the languages involved and their reading skills[3]. Eye tracking could be employed to further explore how this format influences learning outcomes.

## Conclusion

While direct research specifically focused on interlinear text is sparse, existing studies on eye movements during reading provide valuable insights into how different formats can affect cognitive processing. Future research could benefit from applying eye tracking to explicitly examine interlinear text's impact on reading efficiency and comprehension across various languages. This approach would enhance our understanding of how learners interact with bilingual texts and inform best practices in language education.

Citations:
[1] https://lt.cityu.edu.hk/dec/lt-repo/201617/dec-201617-tpg-mals-LT6580-ddhuang6.pdf
[2] https://pmc.ncbi.nlm.nih.gov/articles/PMC9896260/
[3] https://pmc.ncbi.nlm.nih.gov/articles/PMC10741511/
[4] https://www.linkedin.com/pulse/eye-movement-during-reading-andrew-johnson
[5] https://www.researchgate.net/publication/24281505_Eye_movements_when_reading_text_messaging
[6] https://www.sciencedirect.com/science/article/abs/pii/S0024384123001444
[7] https://www.semanticscholar.org/paper/An-eye-tracking-study-of-how-font-size-and-type-Beymer-Russell/501066ccf251484eabff32fb1d5dd93faac5716d
[8] https://www.researchgate.net/publication/299599157_Relation_between_Reading_Speed_Eye_Movements_and_Line_Length_in_Japanese_Electronic_Text_Reader

---

Related
How does interlinear text affect reading speed and comprehension
Are there specific eye movement patterns associated with interlinear text
What are the cognitive processes involved in reading interlinear text
How does interlinear text compare to traditional bilingual texts in terms of readability
What are the benefits of using interlinear text for language learners

---

Citation and abstract for above image.

Hyrskykari, Aulikki & Majaranta, Päivi & Räihä, Kari-Jouko. (2005). From gaze control to attentive interfaces. Interactive applications that make use of eye tracking have traditionally been based on command-and-control. Applications that make more subtle use of eye gaze have recently become increasingly popular in the domain of attentive interfaces that adapt their behaviour based on the visual attention of the user. We provide a review of the main systems and application domains where this genre of interfaces has been used. (Accessed, Research Gate,https://www.researchgate.net/publication/228374956_From_gaze_control_to_attentive_interfaces, 27.11.24.)

Seeming hybrid

A seeming hybrid of interlinear translation would be, for example, hypertext. This is a natural extension of the idea of immediate view of what the source language conveys. 

The hyperlink is the essence of hypertext, and from the beginning of its invention by Tim Berners-Lee, we had online and off- documents linked to quick explication, among other uses. 

About fifteen or more years ago we saw the introduction of tooltips where when the cursor/mouse pointer hovered over something so-linked with this feature, we immediately got information built into the tip code. 

Now, at least for Google's Chrome, there is an extension with the transparent name of MouseTooltipTranslator. The tooltip now links not to the information built into the tip but to a service to give content-context specific translations.

Below is what it looks like . . . works like any tooltip but the info provided is word, phrase, sentence and more translation into the document reader's chosen target language.

This certainly accomplishes the functionality of interlinear translation displays, and it may be preferable for some who want either just what-it-means as well as those interested in the map to the source for text analysis, language learning, etc.

GlossySnake

Github has a number of projects categorized as interlinear. Do a search and see what comes your way.

Meanwhile . . . 

This is an ambitious project which promises(?) a sophisticated interlinear translation web application.

https://glossysnake.com/

The project repository is here.

https://github.com/parkchamchi/GlossySnake

The readme in the repository is a nice discussion of all matters interlinear.

References include the Hamilton method of teaching languages. 

See https://theamericanscholar.org/the-new-old-way-of-learning-languages/

for some background on this and related methods.