Audio · Text / Customer Service
Speech Recognition Dataset [Customer Calls] – Transcribed support conversations for training voice AI systems
Advertised by providerLicensing rights not independently verifiedPaid licence
Overview
Speech Recognition Dataset [Customer Calls] – Transcribed support conversations for training voice AI systems is an audio and text dataset. Typical applications include speech recognition, fine-tuning & instruction data, conversational AI and 1 more. Relevant sectors: Customer Service, Education and AI & Machine Learning. The listing mentions transcription, timestamps and sentiment labels. It is offered as a paid dataset; pricing details are provided on request.
Primary applications
What the listing offers
- Listing mentions transcription, timestamps, sentiment labels.
This dataset is designed for building and improving speech recognition systems. It features transcribed customer service calls from real interactions across 160+ industries, including retail, banking, telecom, logistics, healthcare, and entertainment. Calls are natural, unscripted, and emotion-rich — making the data especially valuable for training models that must interpret speech under real-world conditions. Each dataset entry includes: - Full call transcription (agent + customer dialogue) - Human-written call summary - Overall sentiment label: positive, neutral, or negative - Metadata: call duration, caller location (city, state, country), timestamp - Optional: company name and industry tag Use this dataset to: - Train speech-to-text models on real customer language patterns. -Benchmark or evaluate speech recognition tools in support settings - Improve voice interfaces, chatbots, and IVR systems. - Model tone, frustration cues, and escalation behaviors - Support LLM fine-tuning for tasks involving spoken input.s This dataset provides your speech recognition models with exposure to genuine customer conversations, helping you build tools that can listen, understand, and act in line with how people actually speak. The larger the volume you purchase, the lower the price will be.
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