transcribe-compare 0.2.3

Voicegain Compare transcription

Utility to compare output transcript to reference

Uses Ukkonen algorithm to efficiently compute Leveshtein distance and character error rate (CER).

Additionally it can output alignment information.

Usage

Usage: transcribe-compare [OPTIONS]

  Transcription compare tool provided by VoiceGain

Options:
  -r, --reference TEXT            source string
  -o, --output TEXT               target string
  -R, --reference_file FILENAME   source file path
  -O, --output_file FILENAME      target file path
  -a, --alignment                 Do you want to see the alignment result?
                                  True/False
  -e, --error_type [CER|WER]
  -j, --output_format [JSON|TABLE]
  -l, --to_lower                  Do you want to lower all the words?
                                  True/False
  -p, --remove_punctuation        Do you want to remove all the punctuation?
                                  True/False
  -P, --to_save_plot              Do you want to see the windows? True/False
  -s, --to_edit_step INTEGER      Please enter the step
  -w, --to_edit_width INTEGER     Please enter the width
  --help                          Show this message and exit.

Dependencies

• click
• inflect
• re
• nltk
• metaphone
• matplotlib

Sample Commands

python transcribe-compare -R sample_data/The_Princess_and_the_Pea-reference.txt -O sample_data/The_Princess_and_the_Pea-output-1.txt -e CER

HTML Output

Related code

There is a script available that using transcribe-compare to compare results from Voicegaing and Google recognizers. You can find it here: https://github.com/voicegain/platform/tree/master/utility-scripts/test-transcribe

Acknowledgements

Contributed by VoiceGain.

VoiceGain provides Deep-Neural-Network-based Speech-to-Text (ASR) available in Cloud and also as an Edge Deployment. Accessible via RESTful Web API or MRCP v2 interface. Is suitable both for continuous large-vocabulary transcription (real-time or off-line) and for recognition using context-free grammars (e.g. GRXML). In addition to this VoiceGain platform provides API-driven method to modify models used in speech-to-text. It is possible to modify language model, pronunciation model, and the acoustic DNN model.

License

MIT © VoiceGain