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 Sphinx3 ASR system, to see how different acoustic and language models compare to each other.
The evaluation script relies on SoX being installed, and the Sphinx3 python bindings. The latter can be installed using the install-sphinx.sh script, e.g. on Ubuntu 12.04:
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
See 'COPYING' and 'AUTHORS' files. The audio and transcripts are made available on the BBC web site under personal non-commercial terms of use