The latest
ASAPP tops ASR leaderboard with E‑Branchformer
See how ASAPP speech scientists recently developed the most accurate ASR model. Read more

Kwangyoun Kim
Senior Speech Scientist at ASAPP
Designing AutoCompose
While designing AutoCompose, the ASAPP design team turned down the noise in the agents’ workflow to give them a UI that signals the right suggestions at the right time. Read more

Min Kim
Staff Designer
Not all automation is the same
Where is automation the most impactful? Our AI models specialize in automating even the most difficult parts of customer interactions. Read more

Heather Reed, PhD
Data Scientist, ASAPP
How to start assessing and improving the way your agents use their tools
Empower your leaders to make data-driven, impactful improvements in the call center. JourneyInsight helps you understand customer problems and which tools agents use. Read more

Adrian Botta
Data Scientist
To measure the performance of Conversational AI, we need more strict, better quality benchmarks
For conversational AI to advance, the broader scientific community must be able to work together and explore with easily accessible state-of-the-art baselines for fair performance comparisons. Read more

Suwon Shon, PhD
Senior Speech Scientist at ASAPP
A contact center case study about call summarization strategies
Is your call summarization strategy failing you? Learn from a large enterprise contact center’s mistakes. Read more

Gonzalo Chebi, PhD
Data Scientist
How to Understand Different Levels of AI Systems
Understanding the level of an AI system can help predict how the system will change over time – whether it will continuously improve, remain the same, or even degrade. Read more

Michael Griffiths
Data Scientist, ASAPP
Bringing State of the Art Speech Transcription to CX
End-to-end architecture improves the scalability and performance of machine learning models for speech transcription to serve enterprise contact center needs better. Read more

Prashant Sridhar
Engineering Manager
Wav2vec could be more efficient, so we created our own pre-trained ASR Model for better Conversational AI.
Wav2vec 2.0 is arguably the most popular approach for using self-supervised training in speech, but it could be more efficient. We introduce SEW for better efficiency and performance. Read more

Felix Wu, PhD
Research Scientist at ASAPP
Designed to be proficient on day 1
By combining an intuitive user experience with AI-driven recommendations, you can radically improve the onboarding process. Here’s our approach to making agents successful, faster. Read more

Brad Stell
VP, Product Design