Eric Bolo is the CTO of Batvoice Technologies, a speech analytics startup based in Paris, France. Eric talks about building a custom speech-to-text system for their flagship product, Call Watch.

He introduces us to speech analytics and audio-mining, and describes some typical applications. We go into detail about speech-to-text (STT) technologies, and discuss the pros and cons of using cloud STT services such as Google speech versus building a custom STT system yourself.

Eric tells us about the latest open source tools and frameworks for building STT systems, and how to get that precious voice data to train our models. We learn how to build and annotate a custom voice dataset ourselves, and hear his advice on starting a voice first company.

This is a great first episode to kick off the series! Eric is super smart, with excellent technical skills and a real passion for voice technology. We already know each other quite well, so I couldn't think of anyone I'd rather have as my first guest on the show. I know you're gonna enjoy hearing what he had to say!

#001 - Speech to Text - Eric Bolo, Batvoice - CLIP 1

#001 - Speech to Text - Eric Bolo, Batvoice - CLIP 2

Florian Eyben is the CTO of audEERING, an audio analysis company that specialises in emotional artificial intelligence. Florian is a leading expert in voice emotion analytics, machine learning and signal processing, and our conversation is a great introduction to harnessing emotion in the voice. We discuss many of the incredible applications of voice emotion analytics, and dive into some projects carried out by audEERING for major brands in market research, call centers, social robotics, health and many more.  

In the second half of the episode we explore openSMILE, audEERING's open source research toolkit for audio feature extraction. It is currently the state-of-the-art in affective computing for audio, and is the most widely-used tool for emotion recognition tasks in research and industry. 

We also discuss the GeMAPS standard acoustic parameter recommendation, emotional dimensions such as valence and arousal, what data to use when developing emotion detection algorithms, and the future of multimodal emotion-enabled interfaces. It's an emotion-filled episode that you won't want to miss!

Links from the show:
Full show notes: https://voicetechpodcast.com 
Alexa skill building guide: https://voicetechpodcast.com/skillguide
audEERING site: https://www.audeering.com 
audEERING on Facebook: http://bit.ly/aud-facebook 
audEERING on Twitter: @audEERING
audEERING on Instagram: audEERING
audEERING on LinkedIn: http://bit.ly/aud-linkedin 
openSMILE: https://opensmile.audeering.com 
GeMAPS:  https://ieeexplore.ieee.org/document/7160715
Florian Eyben Google Scholar: http://bit.ly/florian-eyben-scholar 
ICASSP 2019:  https://2019.ieeeicassp.org/
VoiceBot podcast: http://voicebot.ai

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Email me: carl@voicetechpodcast.com

Voice Emotion Analytics - Florian Eyben, audEERING - Voice Tech Podcast ep.014 - CLIP 2

Host of the Voice Tech Podcast. Interviews with voice technology professionals, boosting your knowledge and technical skills. Voice interfaces, voice assistants, data science, machine learning and much more. Subscribe now!

technology, tech, voice, speech, assistant, bot, chatbot, alexa, machine learning, artificial intelligence, data science, AI

Voice Emotion Analytics - Florian Eyben, audEERING - Voice Tech Podcast ep.014 - CLIP 2

Voice Tech Podcast

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