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Zensar

Lead the development and optimization of ASR (Automatic Speech Recognition), TTS (Text-to-Speech), NLU (Natural Language Understanding), and LLM-based components for conversational AI applications.
Architect and implement data pipelines for training, evaluating, and deploying speech and language models at scale.
Develop and fine-tune speech recognition, text-to-speech, and natural language understanding (NLU) models.
Evaluate and optimize ASR (Automatic Speech Recognition) and TTS (Text-to-Speech) engines for accuracy, latency, and user experience.
Integrate LLMs (eg, Open AI, GPT, PaLM, BERT, Claude) into conversational workflows to enhance contextual understanding and response generation.
Strong experience with NLP frameworks (spaCy, Transformers) and LLMs.
Proficiency in Python and ML frameworks (TensorFlow, PyTorch).
Design and implement speech analytics solutions for: call categorization, call tagging, sentiment analysis and trend analysis