Skip to content

Latest commit

 

History

History
60 lines (39 loc) · 2.51 KB

File metadata and controls

60 lines (39 loc) · 2.51 KB

Evaluation script for CMU Sphinx3 on the BBC Reith Lectures

A set of resources to evaluate Sphinx3 in terms of Word Error Rates on the BBC Reith Lectures. The Reith lectures are BBC Programmes made available as podcasts along with their transcripts on the BBC web site, under personal non-commercial terms of use. They cover almost each year since 1976 and a wide range of different speakers.

It can therefore be used for the evaluation of multi-speaker Automated Speech Recognition (ASR) system. In particular, this script helps with evaluating the CMU Sphinx ASR system, to see how different acoustic and language models compare to each other.

However the transcripts are not verbatim. For example quite a few lectures start with an introduction of the speaker, which is not available in the transcripts. Some times, the speaker deviate from the transcripts as well. Therefore the results will often be slightly worse than one could expect.

Dependencies

The evaluation script relies on SoX being installed, and the PocketSphinx python bindings.

apt-get install sox libsox-fmt-mp3 python-numpy python-pocketsphinx

Getting started

Start by downloading the dataset using the provided script.

$ cd reith-lectures

$ ../get-reith-lectures-dataset.sh

Create a configuration file pointing to your acoustic and language models. An example configuration file is given in hub4_and_lm_giga_64k_vp_3gram.ini.example, using the HUB4 acoustic model bundled with Sphinx and a language model derived from the English Gigaword corpus.

Run the evaluation.

$ ./evaluate.py --directory reith-lectures --config sphinx-config.ini

If you want to run the evaluation using only pre-computed transcriptions, use the --lazy flag.

For example to run the evaluation on transcriptions derived using the example configuration file:

$ ./evaluate.py --directory reith-lectures-hub4-and-lm-giga-64k-vp-3gram --lazy true

Average WER: 0.556791

The full results of the above command are available in reith-lectures-hub4-and-lm-giga-64k-vp-3gram/evaluation-results.txt

Licensing terms and authorship

See 'COPYING' and 'AUTHORS' files. The audio and transcripts are made available on the BBC web site under personal non-commercial terms of use