InfoBayAI/Dual-Channel_Audio_Call-Center_Kannada

Dataset Description:

This dataset is a large-scale collection of raw Kannada call center audio (dual-channel), designed to support the development and training of advanced speech and AI systems.

It consists of real-world customer and agent speech recordings collected from call center environments. The dataset is organized in a dual-channel format, where corresponding customer and agent audio are available as separate recordings, enabling clear role-based modeling and analysis. The dataset captures authentic speech characteristics such as tone variation, pauses, silence patterns, and natural speaking behaviour commonly observed in customer service environments.This makes it highly valuable for building accurate, scalable, and production-ready AI systems for enterprise and customer support applications. Additionally, this dataset can be used in data pipelines for Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF) workflows.

Key Use Cases

-Training Automatic Speech Recognition (ASR) systems for call center environments
-Call analytics and conversation intelligence
-Sentiment analysis and emotion detection
-Quality monitoring and compliance analysis
-Virtual assistants for customer support
-Speech-to-Text (STT) for structured call transcription

Dataset Specification

-Language: Kannada
-Type: Raw, unprocessed call center audio
-Speech Style: Customer and agent speech from call center environments
-Audio Conditions: Real-world call center environments
-Domains: customer support, service calls, query resolution, etc.
-Channel Configuration: Dual-channel (separate customer and agent recordings)
-Format: .wav, .mp3, .ogg, etc.
-Sampling Rate: 8000 Hz
-Duration: 9,906 hours

Value of Dual Channel Dataset

-Clear separation of customer and agent speech for accurate modeling
-Supports role-based speech analysis and modeling
-Improves performance in real-world customer support scenarios
-Ideal for call center analytics and conversation intelligence systems
-Facilitates precise annotation and labeling workflows

Basic JSON Schema

{
"id": "string",
"audio_filepath": "string",
"duration": "float",
"language": "string",
"sample_rate": "integer",
"format": "string",
"num_speakers": "integer",
"domain": "string",
"metadata": {
"source": "string",
"recording_condition": "string"
}
}

Full Dataset Overview

Total Duration (in hours): 1,316,582 This dataset is part of a large multilingual podcast audio collection covering the following languages: Arabic, Arabic(EG), Arabic(UG), Assamese, Bengali, Chinese, English (India), English (UK), English (US), Filipino, French, Ganda, German, Gujarati, Hindi, Italian, Japanese, Kannada, Kinyarwanda, Korean, Luganda, Malay, Malayalam, Mandarin, Marathi, Mizo, Nepali, Oriya, Punjabi, Russian, Somali (SO), Somali (UG), Spanish (MX), Spanish (ES), Swahili (KE), Swahili (UG), Tamil, Telugu, Tigrinya, Urdu and Yoruba.

Data Creation

Procured through formal agreements and generated in the ordinary course of business.

Considerations

This dataset is provided for research and educational purposes only. It contains only sample data. For access to the full dataset and enterprise licensing options, please visit our website InfoBay AI or contact us directly.

-Ph: (91) 8303174762
-Email: vipul@infobay.ai