Body: <p>I am currently trying to implement an <em>end-to-end speech recognition</em> system from scratch, that is, without using any of the existing frameworks (like TensorFlow, Keras, etc.). I am building my own library, where I am trying to do a polynomial approximation of functions (like exponential, log, sigmoid, ReLU, etc). I would like to have access to a nice description of the neural networks involved in an end-to-end speech recognition system, where the architecture (the layers, activation functions, etc.) is clearly laid out, so that I can implement it.</p>
  
  <p>I find most of the academic or industry papers citing various previous works, toolkits or papers, making it tedious for me. I am new to the field, so I am having more difficulty, so looking for some help here. </p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-11T11:23:23.823Z
Comments.Text: I took the term "Large Vocabulary Continuous Speech Recognition" while reading Jurafsky-Martin book and I think it implies converting speech-to-text any real world conversation like the Wall-Street-Journal Corpus or the SwitchBoard Corpus. Unlike small datasets these have words of order of thousands covering a genre of words used. Also I came across the latest trend on "End-to-End speech recognition" papers by Baidu, Google and Microsoft. I am fine with any approach for getting me started to implement my ideas.
Comments.UserDisplayName: Jaswin
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-11T17:46:27.630Z
Comments.Text: Welcome to AI.SE @jaswin. Can you include some links to papers you have already read? Are you looking for a description of the _architecture_ of a speech recognition network, or something else? It sounds like maybe you are curious about lower level concepts?
Comments.UserDisplayName: John Doucette
Tags: <neural-networks><natural-language-processing><research><reference-request><speech-recognition>
Title: Is there a detailed description or implementation of an end-to-end speech recognition system?
UserDisplayName: Jaswin
ThreadText: # Is there a detailed description or implementation of an end-to-end speech recognition system?
  
  (Asked by: username_0 on 2019-11-09)
  
  I am currently trying to implement an *end-to-end speech recognition* system from scratch, that is, without using any of the existing frameworks (like TensorFlow, Keras, etc.). I am building my own library, where I am trying to do a polynomial approximation of functions (like exponential, log, sigmoid, ReLU, etc). I would like to have access to a nice description of the neural networks involved in an end-to-end speech recognition system, where the architecture (the layers, activation functions, etc.) is clearly laid out, so that I can implement it.
  
  I find most of the academic or industry papers citing various previous works, toolkits or papers, making it tedious for me. I am new to the field, so I am having more difficulty, so looking for some help here.
  
  **Tags:** neural-networks, natural-language-processing, research, reference-request, speech-recognition
  
  > **Comments:**
  > **username_0**: I took the term "Large Vocabulary Continuous Speech Recognition" while reading Jurafsky-Martin book and I think it implies converting speech-to-text any real world conversation like the Wall-Street-Journal Corpus or the SwitchBoard Corpus. Unlike small datasets these have words of order of thousands covering a genre of words used. Also I came across the latest trend on "End-to-End speech recognition" papers by Baidu, Google and Microsoft. I am fine with any approach for getting me started to implement my ideas.  
  > **username_1**: Welcome to AI.SE @username_0. Can you include some links to papers you have already read? Are you looking for a description of the _architecture_ of a speech recognition network, or something else? It sounds like maybe you are curious about lower level concepts?  
  
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  ## 0 answers
  
  