Audio Call Dataset [Natural] – Authentic customer service recordings for speech modeling and AI training

This dataset comprises natural, unscripted audio recordings from real-world customer service calls, providing high-quality material for training speech-aware AI systems, automatic transcription engines, and customer experience analytics. All recordings are: - Original, not synthetically generated - Captured from real customer-agent interactions across 160+ industries - Available in multiple formats (OGG, FLAC) and aligned with transcriptions Each record includes: -Raw audio file of the customer service call (typically 3–15 minutes) -Accompanying human transcription and summary -Call duration, timestamp, and caller location (city, state, country) -Sentiment label: positive, neutral, or negative Use this dataset to: - Train speech-to-text models using real-world, non-scripted data. - Build natural voice interaction systems or audio-aware LLMs - Simulate real support situations for AI customer service agents. - Perform acoustic sentiment analysis across tones, pauses, and speech speed. - Support multilingual or accent-aware voice modeling (future expansion possible). The dataset reflects the complexity of real communication: interruptions, overtalk, informal language, and emotional variation — perfect for teams working on voice interfaces, speech analytics, and conversational AI.