Takaaki Hori

Takaaki Hori
  • Biography

    Before joining MERL in 2015, Takaaki spent 15 years doing research on speech and language technology at Nippon Telegraph, and Telephone (NTT) in Japan. His work includes studies on speech recognition algorithms using weighted finite-state transducers (WFSTs), efficient search algorithms for spoken document retrieval, spoken language understanding, and automatic meeting analysis.

  • News & Events

    •  NEWS   MERL presenting 9 papers at ICASSP 2018
      Date: April 15, 2018 - April 20, 2018
      Where: Calgary, AB
      MERL Contacts: Petros Boufounos; Takaaki Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Philip Orlik; Pu (Perry) Wang
      Research Areas: Signal Processing, Speech & Audio, Computational Sensing, Digital Video, Multimedia
      • MERL researchers are presenting 9 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Calgary from April 15-20, 2018. Topics to be presented include recent advances in speech recognition, audio processing, and computational sensing. MERL is also a sponsor of the conference.

        ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
    •  NEWS   MERL presents 3 papers at ASRU 2017, John Hershey serves as general chair
      Date: December 16, 2017 - December 20, 2017
      Where: Okinawa, Japan
      MERL Contacts: Chiori Hori; Takaaki Hori; Jonathan Le Roux
      Research Areas: Multimedia, Speech & Audio, Computer Vision, Machine Learning
      • MERL presented three papers at the 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), which was held in Okinawa, Japan from December 16-20, 2017. ASRU is the premier speech workshop, bringing together researchers from academia and industry in an intimate and collegial setting. More than 270 people attended the event this year, a record number. MERL's Speech and Audio Team was a key part of the organization of the workshop, with John Hershey serving as General Chair, Chiori Hori as Sponsorship Chair, and Jonathan Le Roux as Demonstration Chair. Two of the papers by MERL were selected among the 10 finalists for the best paper award. Mitsubishi Electric and MERL were also Platinum sponsors of the conference, with MERL awarding the MERL Best Student Paper Award.

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  • Awards

    •  AWARD   MERL's Speech Team Achieves World's 2nd Best Performance at the Third CHiME Speech Separation and Recognition Challenge
      Date: December 15, 2015
      Awarded to: John R. Hershey, Takaaki Hori, Jonathan Le Roux and Shinji Watanabe
      MERL Contacts: Takaaki Hori; Jonathan Le Roux
      Research Areas: Multimedia, Speech & Audio
      • The results of the third 'CHiME' Speech Separation and Recognition Challenge were publicly announced on December 15 at the IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2015) held in Scottsdale, Arizona, USA. MERL's Speech and Audio Team, in collaboration with SRI, ranked 2nd out of 26 teams from Europe, Asia and the US. The task this year was to recognize speech recorded using a tablet in real environments such as cafes, buses, or busy streets. Due to the high levels of noise and the distance from the speaker's mouth to the microphones, this is very challenging task, where the baseline system only achieved 33.4% word error rate. The MERL/SRI system featured state-of-the-art techniques including multi-channel front-end, noise-robust feature extraction, and deep learning for speech enhancement, acoustic modeling, and language modeling, leading to a dramatic 73% reduction in word error rate, down to 9.1%. The core of the system has since been released as a new official challenge baseline for the community to use.
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  • Research Highlights

  • Internships with Takaaki

    • MM1132: End-to-end acoustic analysis recognition and inference

      MERL is looking for an intern to work on fundamental research in the area of end-to-end acoustic analysis, recognition, and inference using machine learning techniques such as deep learning. The intern will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for high impact publication. The ideal candidate would be a senior Ph.D. student with experience in one or more of source separation, speech recognition, and natural language processing including practical machine learning algorithms with related programming skills. The duration of the internship is expected to be 3-6 months. Positions are available throughout 2018.

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  • MERL Publications

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  • MERL Issued Patents

    • Title: "Method and System for Role Dependent Context Sensitive Spoken and Textual Language Understanding with Neural Networks"
      Inventors: Hori, Chiori; Hori, Takaaki; Watanabe, Shinji; Hershey, John R.
      Patent No.: 9,842,106
      Issue Date: Dec 12, 2017
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