format doc

doc/src/asr_postprocess.md

@@ -99,4 +99,3 @@
 ## Text Filter
 
 * 敏感词（黄暴、涉政、违法违禁等）
-

doc/src/dataset.md

@@ -13,4 +13,3 @@
 * [Tatoeba](https://tatoeba.org/cmn)
 
   **Tatoeba is a collection of sentences and translations.** It's collaborative, open, free and even addictive. An open data initiative aimed at translation and speech recognition.
-

doc/src/ngram_lm.md

@@ -86,5 +86,3 @@ Please notice that the released language models only contain Chinese simplified
    ```
    build/bin/build_binary ./result/people2014corpus_words.arps ./result/people2014corpus_words.klm
    ```
-
-

doc/src/reference.md

@@ -1,4 +1,3 @@
 # Reference
 
 * [wenet](https://github.com/mobvoi/wenet)
-

doc/src/server.md

@@ -31,4 +31,4 @@ Now, in the client console, press the `whitespace` key, hold, and start speaking
 
 Notice that `deepspeech/exps/deepspeech2/deploy/client.py` must be run on a machine with a microphone device, while `deepspeech/exps/deepspeech2/deploy/server.py` could be run on one without any audio recording hardware, e.g. any remote server machine. Just be careful to set the `host_ip` and `host_port` argument with the actual accessible IP address and port, if the server and client are running with two separate machines. Nothing should be done if they are running on one single machine.
 
-Please also refer to `examples/aishell/local/server.sh`, which will first download a pre-trained Chinese model (trained with AISHELL1) and then start the demo server with the model. With running `examples/aishell/local/client.sh`, you can speak Chinese to test it. If you would like to try some other models, just update `--checkpoint_path` argument in the script.  
+Please also refer to `examples/aishell/local/server.sh`, which will first download a pre-trained Chinese model (trained with AISHELL1) and then start the demo server with the model. With running `examples/aishell/local/client.sh`, you can speak Chinese to test it. If you would like to try some other models, just update `--checkpoint_path` argument in the script.  

doc/src/speech_synthesis.md

@@ -142,4 +142,4 @@ HMM 应用到 TTS 这里和 ASR 还是有些区别的。主要参考的论文是
 
 * https://slyne.github.io/%E5%85%AC%E5%BC%80%E8%AF%BE/2020/09/26/TTS/
 * https://slyne.github.io/%E5%85%AC%E5%BC%80%E8%AF%BE/2020/10/25/TTS2/
-* https://slyne.github.io/%E5%85%AC%E5%BC%80%E8%AF%BE/2020/12/04/TTS6/
+* https://slyne.github.io/%E5%85%AC%E5%BC%80%E8%AF%BE/2020/12/04/TTS6/

doc/src/text_front_end.md

@@ -4,7 +4,7 @@
 
 ## Text Segmentation
 
-There are various libraries including some of the most popular ones like NLTK, Spacy, Stanford CoreNLP that that provide excellent, easy to use functions for sentence segmentation. 
+There are various libraries including some of the most popular ones like NLTK, Spacy, Stanford CoreNLP that that provide excellent, easy to use functions for sentence segmentation.
 
 * https://github.com/bminixhofer/nnsplit
 * [DeepSegment](https://github.com/notAI-tech/deepsegment)  [blog](http://bpraneeth.com/projects/deepsegment) [1](https://praneethbedapudi.medium.com/deepcorrection-1-sentence-segmentation-of-unpunctuated-text-a1dbc0db4e98) [2](https://praneethbedapudi.medium.com/deepcorrection2-automatic-punctuation-restoration-ac4a837d92d9) [3](https://praneethbedapudi.medium.com/deepcorrection-3-spell-correction-and-simple-grammar-correction-d033a52bc11d)  [4](https://praneethbedapudi.medium.com/deepsegment-2-0-multilingual-text-segmentation-with-vector-alignment-fd76ce62194f)
@@ -147,4 +147,4 @@ TN: 基于规则的方法
 
 
 ## Reference
-* [Text Front End](https://slyne.github.io/%E5%85%AC%E5%BC%80%E8%AF%BE/2020/10/03/TTS1/)
+* [Text Front End](https://slyne.github.io/%E5%85%AC%E5%BC%80%E8%AF%BE/2020/10/03/TTS1/)