Sonosco (from Lat. sonus - sound and nōscō - I know, recognize) is a library for training and deploying deep speech recognition models.

The goal of this project is to enable fast, repeatable and structured training of deep automatic speech recognition (ASR) models as well as providing a transcription server (REST API & frontend) to try out the trained models for transcription. Additionally, we provide interfaces to ROS in order to use it with the anthropomimetic robot Roboy.

The following diagram shows a brief overview of the functionalities of sonosco:


The project is split into 4 parts that correlate with each other:

For data(-processing) scripts are provided to download and preprocess some publicly available datasets for speech recognition. Additionally, we provide scripts and functions to create manifest files (i.e. catalog files) for your own data and merge existing manifest files into one.

This data or rather the manifest files can then be used to easily train and evaluate an ASR model. We provide some ASR model architectures, such as LAS, TDS and DeepSpeech2 but also individual pytorch models can be designed to be trained.

The trained model can then be used in a transcription server, that consists of a REST API as well as a simple Vue.js frontend to transcribe voice recorded by a microphone and compare the transcription results to other models (that can be downloaded in our Github repository).

Further we provide example code, how to use different ASR models with ROS and especially the Roboy ROS interfaces (i.e. topics & messages).