Jithendra Vepa

CEO

Bengaluru, Karnataka, India26 yrs 8 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Co-founder and CTO of Observe.AI
Expert in machine learning and speech technologies
Over 50 international publications and several patents

Stackforce AI infers this person is a leader in AI-driven speech technology and biomedical signal processing.

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Skills

Core Skills

Machine LearningSpeech TechnologiesBiomedical Signal ProcessingSignal Processing

Other Skills

Speech RecognitionArtificial IntelligenceAutomatic Speech RecognitionText-to-SpeechSpeech TechnologyAlgorithmsLarge Vocabulary Speech RecognitionSpeech SynthesisText-to-Speech SynthesisDigital Signal ProcessingHTKfestivalBiomedical EngineeringMatlabEmbedded Systems

About

Several years of experience in research and development using machine learning (esp. deep learning) & signal processing techniques. Expertise in Machine learning (mainly Hidden Markov models, neural networks (Multi-layer peceptron (MLP), Deep Neural Networks, Recurrent Neural Networks), support vector machines (SVM), and decision trees) and Speech technologies (automatic speech recognition (ASR), text-to-speech synthesis (TTS), natural language processing (NLP), and blind source separation) Worked in diverse domains such as Speech technologies,Bio-medical signal processing and collaborated with teams across different geographies (UK, US, Switzerland, South Korea, etc). Blended with technical and management skills Experience in building strong technical teams by hiring right talent and mentoring, also in supervising graduate students More than 50 international publications in peer-reviewed conferences and journals. Several patents filed in voice assistants and bio-medical signal processing.

Experience

Observe.ai

Co-founder & CTO

Sep 2018 – Present · 7 yrs 6 mos · Bengaluru Area, India

Observe.AI is an Intelligent Workforce Platform that transforms contact centers by embedding AI into 100% of customer conversations, optimizing agent performance, and automating repeatable processes that drive revenue and retention.
Observe.AI is trusted by hundreds of customers and partners, including 23&Me, 2U, Alcon Laboratories, Concentrix, National Debt Relief, and Pearson. Backed by $88M in total funding from Menlo Ventures, Scale Ventures, Nexus Ventures, Next47, NGP Capital, Emergent Ventures, and Y-Combinator, Observe.AI’s headquarters is in San Francisco with an office in Bangalore, India. For more information, visit www.observe.ai.

Speech RecognitionMachine LearningArtificial IntelligenceSignal ProcessingSpeech Technologies

Samsung research & development india -- bangalore

Senior Principal Engineer

Nov 2009 – Sep 2018 · 8 yrs 10 mos · Bangalore

Built a speech technology team from the ground up and developed automatic speech recognition (ASR) and text-to-speech (TTS) systems for Samsung flagship products.

Automatic Speech RecognitionText-to-SpeechSpeech TechnologySpeech TechnologiesMachine Learning

Philips research

Senior Research Scientist

Mar 2007 – Nov 2009 · 2 yrs 8 mos · Bangalore

Research on biomedical signal processing, and developing algorithms for noise cancellation, segmentation and classification of biomedical signals.

Biomedical Signal ProcessingAlgorithmsSignal Processing

Idiap research institute

Research Scientist

Mar 2004 – Feb 2007 · 2 yrs 11 mos · Martigny, Switzerland

Research on automatic speech recognition (ASR), large vocabulary speech recognition (LVCSR) development for AMI project, NIST RT evaluation participation

Automatic Speech RecognitionLarge Vocabulary Speech RecognitionSpeech Technologies

Center for speech technology research, university of edinburgh

PhD Student

Oct 2000 – Jan 2004 · 3 yrs 3 mos · Edinburgh, United Kingdom

Thesis title: Join Cost in Unit Selection Speech Synthesis
During first part of my research, I investigated various spectral-based distance measures for use in computation of the join cost by designing a perceptual listening experiment, and proposed new spectral distance measures, which have good correlation with human perception to concatenation discontinuities.
The second part of my research concentrates on combining join cost computation and smoothing operation, which required to disguise joins, by learning an underlying representation from the acoustic signal.

Speech SynthesisSignal ProcessingSpeech Technologies