Milestone 8 – Evaluating performance across datasets
As we conclude our Whisper fine-tuning journey, validating model performance across diverse real-world conditions represents a pivotal final milestone. Before deploying our optimized speech recognizer into production scenarios, comprehensively assessing its effectiveness across datasets, languages, accents, and acoustic environments is essential for instilling confidence. This testing phase unveils actual capabilities, revealing where additional tuning may be required while spotlighting areas suitable for immediate application. The rigorous evaluation processes outlined in this section aim to verify customized performance gains while guiding ethical and inclusive rollout by covering key facets such as bias mitigation, domain optimization, translation abilities, and expectation management.
Mitigating demographic biases
Machine learning models, including those for speech recognition, can sometimes detect biases against...
