This dataset is a large-scale multilingual podcast audio corpus designed for training and evaluating Automatic Speech Recognition (ASR), Speech-to-Text (STT), Speech AI, Voice AI, Conversational AI, Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs).
The corpus contains over 57,000 hours of podcast audio collected from diverse podcast formats, speakers, topics, and conversational styles. The dataset includes both single-channel and dual-channel recordings, enabling a wide range of speech processing, speaker modeling, transcription, and conversational AI applications.
The audio captures authentic human speech with natural accents, speaking styles, conversational dynamics, pauses, interruptions, emotional variation, and real-world recording conditions, making it suitable for enterprise AI development and research.
Key Use Cases
Automatic Speech Recognition (ASR)
Speech-to-Text (STT)
Conversational AI and Voice AI
Podcast transcription systems
Large Language Model (LLM) training
Supervised Fine-Tuning (SFT)
Retrieval-Augmented Generation (RAG)
Speaker diarization and speaker identification
Sentiment and intent analysis
Audio understanding and speech analytics
AI assistants and virtual agents
Dataset Features
57,000+ hours of podcast audio
Multilingual speech content
Single-channel and dual-channel recordings
Real-world conversational speech
Diverse speakers and accents
Broad topical coverage
Long-form audio content
Suitable for AI training and evaluation workflows
Foundation model and speech model development
Content Coverage
The dataset includes podcast content spanning a wide range of domains such as:
Technology and Artificial Intelligence
Business and Entrepreneurship
Finance and Economics
Healthcare and Medicine
Education and Learning
Science and Research
News and Current Affairs
Entertainment and Media
Lifestyle and Culture
General Knowledge
This diversity enables the development of domain-aware AI systems capable of understanding varied conversational contexts and specialized terminology.
AI Training Applications
The corpus is designed to support modern AI development workflows, including speech foundation model training, ASR development, transcription systems, conversational intelligence, NLP pipelines, multimodal AI systems, and next-generation Generative AI applications.
Organizations can utilize this dataset to develop speech recognition systems, voice assistants, intelligent search platforms, podcast analytics solutions, customer interaction systems, and multilingual AI applications.
Data Collection
The dataset consists of multilingual podcast audio collected and organized to support large-scale machine learning, speech processing, and artificial intelligence workflows. The corpus provides extensive linguistic, topical, and conversational diversity suitable for both research and commercial AI applications.
Licensing & Access
This listing contains sample data intended for research, evaluation, and educational purposes. Enterprise licensing and access to the full dataset are available upon request.
57,000+ hours of multilingual podcast audio featuring diverse speakers, accents, topics, interviews, discussions, and real-world conversational speech.
Includes single-channel and dual-channel recordings optimized for ASR, Speech Recognition, Speech-to-Text (STT), Voice AI, and Conversational AI applications.
Designed for LLM training, Supervised Fine-Tuning (SFT), RAG, podcast transcription, speaker diarization, NLP, and Generative AI development workflows.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
This listing carries a single pricing dimension: Product Access (Units), which grants subscribers access to the dataset at no charge. There are no tiers, instance sizes, or usage-based add-ons to compare. You subscribe once to unlock access. The dataset covers multilingual podcast audio in single and dual channel formats. Because pricing is free, there is nothing that scales with volume, language count, or usage. Access is uniform for all subscribers under this one dimension.
Top-of-mind questions for buyers
What does one unit of Product Access grant me for this dataset?
One unit grants subscriber access to the multilingual podcast audio dataset. This covers single and dual channel podcast speech recordings. Access is uniform for every subscriber. There is no per-hour, per-language, or per-recording metering tied to the unit.
Does my cost change if I use more languages, hours, or channel formats?
No. Pricing is free under a single access dimension. Nothing scales with the number of languages, the volume of audio hours, or whether you use single or dual channel recordings. Your access stays the same no matter how much of the dataset you use.
What audio content and metadata come with the podcast dataset access?
You get podcast speech recordings in single and dual channel formats. Recordings carry metadata such as gender, age, industry, channel, dialect, and language. Delivery uses WAV or FLAC audio with JSON transcripts and a metadata file. Diarization files ship with dual channel audio.
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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.