Research Index
Published research in voice and AI/ML
Explore research breakthroughs at the intersection of voice technology, AI, and machine learning. From reducing transcription errors in noisy environments to improving spoof detection against synthetic voices, we offer practical solutions to complex challenges in enterprise contact centers.
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LLM Selection: Improving ASR Transcript Quality via Zero-Shot Prompting
Large Language Models (LLMs)
Sparse Autoencoder insights on voice embeddings
Speech Recognition
Echoes unveiled: Identifying synthetic voices
Natural Language Processing
Efficient and verifiable responses using Retrieval Augmented Generation (RAG)
Large Language Models (LLMs)
How Susceptible are LLMs to Logical Fallacies?
Large Language Models (LLMs)
Evaluating feature importance for speaker separation models
Speech Processing
Digits micro-model for accurate and secure transactions
Machine Learning
Text Summarization for Call Center Transcripts
Generative AI
Improved Named Entity Recognition for Noisy Call Center Transcripts
Natural Language Processing
Project Vāc: Can a Text-to-Speech Engine Generate Human Sentiments?
Speech Processing
Disambiguation and Error Resolution in Call Transcripts
Speech-to-Text
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