Undergraduate thesis · Speech recognition · 2014
Bangla Speech Corpus For Large Vocabulary ASR System
A speech-corpus and baseline recognition study by Anurag Bhattacharjee and Sujoy Datta, built around standard Bangla as spoken across regions of Bangladesh.
Research question
How can a Bangla speech corpus support a large-vocabulary ASR baseline?
The thesis prepared text, recorded audio, phonetic labels, a pronunciation dictionary and phoneme bigrams, then trained and evaluated a recognition system with the CMUSphinx toolchain.
Text + recordingsregional speech samples
Phonetic resourceslabels + dictionary
SphinxTrainacoustic model
PocketSphinxbaseline evaluation
Evaluation
Report the metric with its meaning and scope.
Approximately 39.39%Performance reported in the 2014 thesis. The corpus and evaluation are best understood as an early baseline with limited training data.
What this establishes
Early experience with speech-corpus construction, phonetic resources, acoustic-model training and ASR evaluation.
How it connects to current work
This undergraduate work is a historical foundation for later NLP research; it is not presented as evidence of current production speech-AI experience.