Speech-to-text
Generating New Customer Intelligence
Contact centers are goldmines of market information, see how AutoSummary elevates actionable insights. 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
Utilizing Pre-trained Language Model for Speech Sentiment Analysis
On the path to real-time speech sentiment analysis, new ASAPP research achieves training efficiency gains with transfer learning between spoken and written language domains. Read more
Suwon Shon, PhD
Senior Speech Scientist at ASAPP
Multi-mode ASR: Increasing Robustness with Dynamic Future Contexts
Rather than maintaining multiple ASR models that work under varying time constraints or conditions, new ASAPP research introduces a single multi-mode model that can dynamically adjust to different scenarios. Read more
Kwangyoun Kim
Senior Speech Scientist at ASAPP
Introducing CLIP: A Dataset to Improve Continuity of Patient Care with Unsupervised NLP
In pursuit of our mission to enhance human performance and automate the world’s workflows, ASAPP is releasing one of the largest annotated datasets for clinical NLP. Read more
James Mullenbach
Research Engineer at ASAPP
Why companies who want true VoC need to engage the power of AI
Engage the power of AI to get rich voice of the customer (VoC) insight that you can act on right now. Build loyalty and grow CLV. Read more
Michael Lawder
Chief Experience Officer, ASAPP
Why a little increase in transcription accuracy is such a big deal
Highly accurate speech-to-text transcription can provide tremendous value, but most off-the-shelf ASR models struggle with the words that matter most. Read more
Austin Meyer
Head of Solution Design at ASAPP
Task-oriented dialogue systems could be better. Here’s a new dataset to help.
Dialogue State Tracking has run its course. That’s why we’re establishing a new Action-Based Conversations Dataset. Read more
Derek Chen
Research Scientist at ASAPP
Addressing instabilities for few-sample BERT fine-tuning
Building on recent advances in natural language processing, new research from Felix Wu identifies ways to significantly stabilize BERT fine-tuning on small datasets. Read more
Felix Wu, PhD
Research Scientist at ASAPP
Filling in the missing pieces for automation
Natural language input can be hard to classify. ASAPP research goes beyond conventional methods, building better systems to inform more accurate automation. Read more
Yoav Artzi
Research Fellow at ASAPP
