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https://github.com/persephone-tools/persephone

A tool for automatic phoneme transcription
https://github.com/persephone-tools/persephone

acoustic-models artificial-intelligence machine-learning neural-networks speech-recognition

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A tool for automatic phoneme transcription

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README 

        
Persephone v0.4.2 (beta version)

================================



**NOTE: This codebase is not actively maintained and development efforts are being placed elsewhere. If you're interested in training a language-specific speech recognition model using ELAN files, consider using Elpis (https://github.com/CoEDL/elpis/). If you're interested in general phonetic transcription using a pre-existing multilingual speech recognition model, consider trying (https://www.dictate.app/).**



Persephone (/pərˈsɛfəni/) is an automatic phoneme transcription tool.

Traditional speech recognition tools require a large pronunciation

lexicon (describing how words are pronounced) and much training data so

that the system can learn to output orthographic transcriptions. In

contrast, Persephone is designed for situations where training data is

limited, perhaps as little as an hour of transcribed speech. Such

limitations on data are common in the documentation of low-resource

languages. It is possible to use such small amounts of data to train a

transcription model that can help aid transcription, yet such technology

has not been widely adopted.



    The speech recognition tool presented here is named after the

    goddess who was abducted by Hades and must spend one half of each

    year in the Underworld. Which of linguistics or computer science is

    Hell, and which the joyful world of spring and light? For each it’s

    the other, of course. --- Alexis Michaud



The goal of Persephone is to make state-of-the-art phonemic

transcription accessible to people involved in language documentation.

Creating an easy-to-use user interface is central to this. The user

interface and APIs are a work in progress and currently Persephone must

be run via a command line.



The tool is implemented in Python/Tensorflow with extensibility in mind.

Currently just one model is implemented, which uses bidirectional long

short-term memory (LSTMs) and the connectionist temporal classification

(CTC) loss function.



We are happy to offer direct help to anyone who wants to use it.

Please use the `discussion mailing list `_ 

to discuss questions regarding this project.

We are also very welcome to thoughts, constructive criticism, help with

design, development and documentation, along with any `bug reports `_ or

`pull requests `_ you may have.



Documentation

=============



Documentation can be found `here `_.



Contributors

============



Persephone has been built based on the code contributions of:



* Oliver Adams

* `Janis Lesinskis `_

* Ben Foley

* Nay San



Citation

========



If you use this code in a publication, please cite `Evaluating Phonemic

Transcription of Low-Resource Tonal Languages for Language

Documentation `_:



::



    @inproceedings{adams18evaluating,

    title = {Evaluating phonemic transcription of low-resource tonal languages for language documentation},

    author = {Adams, Oliver and Cohn, Trevor and Neubig, Graham and Cruz, Hilaria and Bird, Steven and Michaud, Alexis},

    booktitle = {Proceedings of LREC 2018},

    year = {2018}

    }