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Speech Recognition 🗣️ in Bengali 🇧🇩🇮🇳

Overview

ASR project for Bengali, exploring Automatic Speech Recognition (ASR) techniques.

ASR system transcribes speech into text, emphasizing the probabilistic sequence of words and sounds.

Two approaches: statistical and end-to-end. Acoustic Model and Lexicon play key roles.

I focus here on the end-to-end approach.

Bengali Language

  • 09 vowels, 39 consonants
  • Official language of Bangladesh
  • 2nd most spoken language in India

Spoken by 200M+ people, featuring diverse dialects.

Competition Objective

Handling out-of-distribution data and linguistic nuance, improve WER.

Training Database

  • 1180 hours of audio
  • Data cleaning: maintain WER < 70%
  • Preprocessing: Mel-Log Spectrograms, tokenized embeddings

Models Explored

RRN-T Transducer 🔄

PyTorch implementation with transducer approach.

Whisper by OpenAI 🤫

40% WER on Common Voice, 10% in French.

Results 📚

  • Baseline vs. Whisper vs. BenglaASR
  • Whisper-small fine-tuned: WER 67% achieve lower WER then the baseline.

More details presentation slides in French here

Sources: