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Universal Listening Comprehension - Speech-to-Text, Bilingual Subtitle Translation

Alibaba's free large model application, real-time speech recognition, AI subtitle translation, and intelligent summarization. Essential for online courses, chasing dramas, and online meetings. Record, transcribe, translate, and summarize online courses and meetings from any web page.
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Universal Listening Comprehension - Speech-to-Text, Bilingual Subtitle Translation
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Introduction

Ting Wu is an AI-driven platform offering real-time voice recognition, AI-powered subtitles, and smart summarization. It's designed to enhance the experience of online courses, meetings, and video watching by providing efficient transcription and comprehension tools.

Feature

Real-time Voice Recognition

Ting Wu's advanced AI technology enables instant voice recognition, allowing users to effortlessly record and transcribe conversations in real-time.

AI-Powered Subtitles

The platform generates AI-powered subtitles in multiple languages, facilitating easy understanding and translation of audio content across linguistic barriers.

Smart Summarization

Ting Wu's intelligent summarization feature quickly extracts and presents the main points from conversations or meetings, saving users valuable time and effort.

Chrome Integration

Users can easily add Ting Wu to their Chrome browser through the Chrome Web Store, making it readily accessible for various online activities.

Multi-language Support

The platform supports multiple languages, catering to a diverse user base and enhancing its utility in various global contexts.

Free Version Available

Ting Wu offers a free version with 50 hours of transcription time, with daily login rewards of 10 additional hours, making it accessible to a wide range of users.

FAQ

How do I start using Ting Wu?

To begin using Ting Wu:

  1. Install the Ting Wu extension from the Chrome Web Store
  2. Register or login to your account
  3. Select your preferred language
  4. Click "Start Recording" to begin transcription
  5. Share the recording if needed
  6. Click "End Recording" when finished

What are the main applications of Ting Wu?

Ting Wu is particularly useful for:

  • Recording and transcribing online courses
  • Capturing and summarizing meeting content
  • Enhancing video watching experiences with subtitles and summaries

Is Ting Wu free to use?

Yes, Ting Wu offers a free version with the following benefits:

  • 50 hours of initial transcription time
  • 10 additional hours rewarded for daily logins

Can Ting Wu handle multiple languages?

Yes, Ting Wu supports multiple languages for both voice recognition and subtitle generation, making it versatile for various linguistic needs.

Latest Traffic Insights

  • Monthly Visits

    290.25 M

  • Bounce Rate

    55.49%

  • Pages Per Visit

    2.84

  • Time on Site(s)

    113.64

  • Global Rank

    -

  • Country Rank

    -

Recent Visits

Traffic Sources

  • Social Media:
    0.68%
  • Paid Referrals:
    0.54%
  • Email:
    0.11%
  • Referrals:
    14.58%
  • Search Engines:
    15.20%
  • Direct:
    68.89%
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You can now access ChatGPT, a powerful language model, for free with Google. Here's how:

Method 1: Google Colab

* Open Google Colab ([colab.research.google.com](http://colab.research.google.com))
* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`

Method 2: Google Apps Script

* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`

Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.
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Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.

Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.

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