LM在speech recognition中的應用
今天我們來看看language model(簡稱LM)在speech recognition中的應用。 首先來看上圖，LM主要可以預測token sequence 的機率，雖然我們的LAS中其實只需要P(Y|X)的數值即可，但在實際操作中我們還是會加上P(Y)的數值，我們知道P(Y|X)需要的都是成對的數據，但是P(Y)非常容易去收集。 我們可以看看，Google的語音訓練模型一共使用了12500
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- 4. 【論文筆記】Improving Transformer-based End-to-End Speech Recognition with CTC and LM Integration
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相關文章
- 1. speech recognition resource
- 2. Almost Unsupervised Text to Speech and Automatic Speech Recognition
- 3. 5 Open Source Speech Recognition/Speech-to-Text Systems
- 4. 【論文筆記】Improving Transformer-based End-to-End Speech Recognition with CTC and LM Integration
- 5. Convolutional Neural Networks for Speech Recognition///2014
- 6. Visual Speech Recognition: Lip Segmentation and Mapping
- 7. Food Log with Speech Recognition and NLP
- 8. Interspeech 2017 | Far-field Speech Recognition Technology
- 9. 聲音辨識Speech Recognition
- 10. 2019 Interspeech speech emotoin recognition paper reading