Speech ML / DL Data | Customer–Agent Conv. (Single & Multi-Channel & Hard-to-Source Languages) | GDPR, CCPA Compliant | Native Speakers 180+ Countries
Overview
Speech ML / DL Data | Customer–Agent Conv. (Single & Multi-Channel & Hard-to-Source Languages) | GDPR, CCPA Compliant | Native Speakers 180+ Countries is an audio dataset. Typical applications include speech recognition, speaker recognition, fine-tuning & instruction data and 3 more. Relevant sectors: AI & Machine Learning, Education and Manufacturing & Industrial. The listing mentions transcription, timestamps and speaker labels. Pricing is not published and is provided on request.
Primary applications
What the listing offers
- Listing mentions transcription, timestamps, speaker labels.
Scope: Synthetic customer–agent interactions, available in dual-channel (per speaker) or single-channel mixes. Ideal for service, sales, and call center AI. Audio Specs: • Sample rate: 16 kHz, 16-bit • Dual channel or mono per client need • Conversation style: agent–customer (industry-agnostic) • Control over speaker accents, environment, metadata Volume: 50–200 hours typical per project; scalable to 10,000-100,000+ hours. Speakers: Native speakers from our user community, with hard-to-source accents prioritized. Transcripts: Full transcripts with speaker ID, timestamps, diarization. Why Us: • Coverage of underrepresented accents for realistic call center AI • Flexible formats to fit client pipelines • Streamed monthly delivery available for continuous improvement cycles Use Cases: • Call center AI and ASR for telephony • Dialogue state tracking for task-oriented assistants • LLM fine-tuning on service-oriented interactions
Related datasets
More in Video & Physical AI →Speech ML / DL Data | Customer–Agent Conv. (Single & Multi-Channel & Hard-to-Source Languages) | GDPR, CCPA Compliant | Native Speakers 180+ Co
Scope: Synthetic customer–agent interactions, available in dual-channel (per speaker) or single-channel mixes.
- Language
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- Volume
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- Domain
- AI & Machine Learning +2
- Use case
- Speech recognition