American English Call Center
Start training, testing or fine-tuning your speech models with 13,000 hours of American English live, non-simulated call center conversations. In most cases, customers are native English speakers, but the customer service representatives may not be. This channel-separated dataset is perfect for those who are looking for instances of spontaneous speech in call center settings, recorded over telephony for their ASR conversational analysis models.
Start training, testing or fine-tuning your speech models with 13,000 hours of American English live, non-simulated call center conversations. In most cases, customers are native English speakers, but the customer service representatives may not be. This channel-separated dataset is perfect for those who are looking for instances of spontaneous speech in call center settings, recorded over telephony for their ASR conversational analysis models.
Start training, testing or fine-tuning your speech models with 13,000 hours of American English live, non-simulated call center conversations. In most cases, customers are native English speakers, but the customer service representatives may not be. This channel-separated dataset is perfect for those who are looking for instances of spontaneous speech in call center settings, recorded over telephony for their ASR conversational analysis models.
Start training, testing or fine-tuning your speech models with 13,000 hours of American English live, non-simulated call center conversations. In most cases, customers are native English speakers, but the customer service representatives may not be. This channel-separated dataset is perfect for those who are looking for instances of spontaneous speech in call center settings, recorded over telephony for their ASR conversational analysis models.
Dataset specs
Type
Audio
Region/Locale
EN,
en-US
Amount
16K hours
Leverage
Enhance your AI-powered American English call center systems by training models that automatically route calls, respond to queries and generate real-time insights based on customer interactions.
Use cases
Train AI models to analyze call center conversations for sentiment analysis, issue resolution and performance tracking, enabling better agent training and performance management.
Improve ASR models and speaker identification accuracy, resulting in more precise text outputs and better speaker differentiation in real-world call center environments.
Do you need a specific dataset?
We understand the uniqueness of every project. That's why we offer customizable dataset solutions to match your specific requirements.
Dataset specs
Type
Audio
Region/Locale
EN,
en-US
Amount
16K hours