Magic Data has introduced the "Multi-stream Spontaneous Conversation Training Datasets_English".This dataset comprises 5,000 hours of multi-accent English conversational data, encompassing a wide range of vocal scenarios. Our dataset allows AI models to better understand contextual changes, tonal variations, and emotional shifts in conversations, thereby producing responses that are more natural and accurate.
Language
English
Data Style
Conversational Style
Sampling Rate
16kHz
Bit Rate
16bits
Channel
2
Number of Speakers
more than ten thousand individuals
Total Audio Duration
5000+ hours
Recently, the global scientific and technological community is experiencing a flourishing era of voice conversation models. The core of these advanced interactive experiences lies in the naturalness and real-time responsiveness of their conversations. These models not only recognize users’ speech but also simulate responses that are close to human speech. The realization of advanced voice interactions, such as GPT-4o and Google Gemini Live, underscores the critical importance of data quality.
Magic Data has introduced the "Multi-stream Spontaneous Conversation Training Datasets_English," representing a significant technical breakthrough while offering developers enhanced flexibility in application development. This dataset comprises 5,000 hours of multi-accent English conversational data, encompassing a wide range of vocal scenarios. By leveraging multi-channel conversational data, which facilitates the independent analysis of each speaker's voice, AI models can more effectively capture contextual shifts, tonal variations, and emotional nuances. This enables the generation of conversational responses that are both highly natural and precise.
ISO/IEC 27001 & ISO/IEC 27701:2019 compliant
Audio, text, image, and video multi-modal data
Conversational, scripted, and spontaneous data covering extensive domains
Expertise secured quality result