Sold by: InfoBay AI Ltd.
Deployed on AWS
AI training datasets for Speech Recognition (ASR), NLP, Conversational AI, Voicebots, LLM fine-tuning, Healthcare AI, and Multilingual AI applications. Includes 2.12M+ hours of audio data, call center conversations, podcasts, speaker diarization, and human-annotated datasets across multiple languages and domains.
Overview
Enterprise Audio Dataset for Speech AI, Conversational AI & LLM Training
This dataset is a large-scale multilingual audio corpus designed for training and evaluating Speech AI, Conversational AI, Automatic Speech Recognition (ASR), NLP, Generative AI, and LLM-powered enterprise systems.
The dataset includes real-world conversational audio collected across customer support, contact centers, healthcare, podcasts, virtual assistants, enterprise communication, and spontaneous speech environments. The corpus captures authentic conversational characteristics including accents, pauses, silence patterns, emotional variation, overlapping speech, and natural human interactions.
The dataset supports a wide range of enterprise AI applications including ASR systems, Speech-to-Text (STT), Voice AI, Contact Center AI, speaker diarization, sentiment analysis, conversational intelligence, virtual assistants, RLHF pipelines, Supervised Fine-Tuning (SFT), and LLM alignment workflows.
Key features include:
Large-scale multilingual conversational audio Real-world enterprise speech environments Single-channel and dual-channel audio Human-annotated and validation-ready workflows Support for transcription, sentiment labeling, and speaker modeling Production-ready AI training pipelines
The dataset is compatible with modern speech and NLP architectures and can be used for foundation model training, enterprise automation, customer service AI, telecom AI, healthcare AI, and multilingual conversational systems.
Audio quality has been evaluated using industry-standard signal and perceptual quality metrics including DNSMOS, SNR analysis, loudness normalization, clipping analysis, and SQUIM-based evaluation to ensure production-level reliability for AI training workflows.
The multilingual corpus includes audio data across multiple global languages including Arabic, Bengali, Chinese, English, Filipino, French, German, Hindi, Japanese, Korean, Malayalam, Mandarin, Marathi, Punjabi, Russian, Spanish, Swahili, Tamil, Telugu, Urdu, Yoruba, and additional regional languages.
Data is procured through formal agreements and generated during the ordinary course of business operations. Custom data collection, annotation, transcription, validation, and synthetic data generation services are also available based on enterprise requirements.
This listing contains sample data intended for research, evaluation, and educational purposes. Enterprise licensing and full corpus access are available upon request.
InfoBay AI Email: datareq@infobay.ai Phone: +91 8303174762
Highlights
- Large-scale multilingual audio datasets for ASR, Speech Recognition, Conversational AI, Voice AI, and LLM training workflows. Includes real-world conversational speech collected from enterprise and customer support environments.
- Supports enterprise AI applications including Speech-to-Text (STT), Contact Center AI, speaker diarization, sentiment analysis, RLHF, Supervised Fine-Tuning (SFT), and conversational intelligence systems.
- Production-ready AI training data with multilingual coverage, dual-channel audio support, human annotation workflows, and quality validation using DNSMOS, SNR, and perceptual audio evaluation metrics.
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Additional details
You will receive access to the following data sets.
Data set name | Type | Historical revisions | Future revisions | Sensitive information | Data dictionaries | Data samples |
|---|---|---|---|---|---|---|
Multilingual Audio Dataset | All historical revisions | All future revisions | Not included | Not included |
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