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Shinozaki Lab
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The lab studies speech information processing and machine learning, with a focus on speech recognition.
AboutAbout the lab
Computer recognition and understanding of speech
Shinozaki Lab studies speech information processing and machine learning, with a focus on speech recognition.
From an engineering perspective, the lab aims to uncover how humans recognize, understand, and learn speech, and to realize those abilities on computers.
Rather than relying only on speech data with correct labels, the lab works on technologies that learn on their own through unsupervised learning and reinforcement learning.
The basic knowledge mainly needed for the research is mathematics and programming.
Key terms
- Speech recognition
- Technology in which a computer listens to human speech and converts it into words or text
- Unsupervised learning
- A way of learning in which a computer finds rules or groupings on its own from data that has no correct labels
- Reinforcement learning
- A method in which a computer repeats trial and error and learns the actions that maximize the "reward" it receives when it succeeds
ResearchResearch themes
From an engineering perspective, the lab aims to uncover how humans recognize, understand, and learn speech, realize those abilities on computers, and explore their applications. Because supervised learning with labeled speech data has limitations, the lab studies technologies based on unsupervised learning and reinforcement learning that learn on their own from multiple sources of information, such as speech and images.
*Illustrative imageAutomatic acquisition of spoken language
Just as children learn words by imitating the voices around them, the lab studies how a system equipped with a speech synthesizer, a microphone, and a camera can acquire spoken language through reinforcement learning.
*Illustrative imageLearning spoken language without relying on labels
Because supervised learning with labeled speech data has limitations, the lab studies technologies for learning spoken language through semi-supervised and unsupervised learning.
*Illustrative imageSpeech synthesis that imitates the vocal organs
This research produces voice by operating a physical model of the human vocal organs. Combined with deep neural networks, the lab has proposed a method that automatically learns how to operate the model through self-supervised learning.
*Illustrative imageDetecting anomalies by sound
As an application of speech information processing, the lab works on systems that monitor the operating sounds of machines and automatically detect anomalies.
MembersFaculty
The members of Shinozaki Lab consist of faculty, doctoral, master's, and undergraduate students, and administrative assistants.
- ProfessorTakahiro ShinozakiPublications ↗
- Assistant ProfessorSheng LiPublications ↗
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Human voice spectrogram” Dvortygirl, Mysid / CC BY-SA 3.0 (cropped)
- Automatic acquisition of spoken language: “Icub full body” Jll at English Wikipedia / CC BY-SA 3.0 (cropped)
- Learning spoken language without relying on labels: “Long-window reassigned spectrogram of speech” Kelly Fitz / CC BY-SA 3.0 (cropped)
- Speech synthesis that imitates the vocal organs: “Short-window reassigned spectrogram of speech” Kelly Fitz / CC BY-SA 3.0 (cropped)
- Detecting anomalies by sound: “07-Port Propulsion Motor” Dashers at English Wikipedia / Public domain (cropped)
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