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Speech Science Lab
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A speech science lab that studies how voices are produced and how they are heard.
AboutAbout the lab
Exploring how the voice is produced and how it is heard.
In the field of speech science, Assistant Professor Kohei Wakamiya studies how people produce speech and how that sound is perceived.
The research measures the movements of the articulators inside the mouth with a 3D magnetic sensor system, and develops methods for collecting the basic data needed to build speech production models that imitate the mechanisms of human speech.
The lab also works on the intelligibility of degraded speech, the evaluation of hoarse voices, and research on determining infectious disease infection from cough sounds.
Assistant Professor Wakamiya is a faculty member of the Acoustic Design Course in the School of Design.
Key terms
- Articulatory movement
- The movement of the articulators inside the mouth when producing speech.
- Mosaic speech
- Degraded speech made by dividing speech by frequency and time and shaping noise according to the average power of each segment.
- Hoarseness
- A term for a disturbed state of voice quality, such as a husky voice.
- GRBAS
- A scale for rating hoarseness by how it sounds. The name is made from the initials of its five rating items.
ResearchResearch themes
People produce speech by moving their articulators, and speech varies widely in voice quality. This research investigates the mechanisms that produce speech and how speech is perceived and evaluated, through measurement of the articulators and analysis of speech.
Detecting Infectious Disease from Cough Sounds
This research determines from cough sounds whether a person has an infectious disease. It deals with methods for estimating from cough sounds whether a person is healthy or infected.
Intelligibility of Interrupted Speech
With collaborators, the lab examines the intelligibility of mosaic speech, segmented by frequency and time, when it is interrupted. Stretching the sound of the interrupted segments to fill the silent gaps can either increase or decrease intelligibility.
Automatic Evaluation of Hoarse Voice
This research uses deep learning to automatically estimate GRBAS, a rating scale for hoarseness. The lab examines whether estimates close to expert ratings are possible even with little labeled speech data.
*Illustrative imageMeasuring and Analyzing the Mechanisms of Speech
The lab measures and analyzes the movements of the articulators inside the mouth (articulatory movements) with a 3D magnetic sensor system. It studies how to collect the basic data needed to build speech production models that imitate the mechanisms of human speech.
MembersFaculty
- Assistant ProfessorKohei Wakamiya
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 Larynx Model ( )” YVC Biology Department / CC BY 2.0 (cropped)
- Measuring and Analyzing the Mechanisms of Speech: “Glottal Enterprises EG2PCX Electroglottograph” Polishwonder74 (talk) / Public domain (cropped)
- Related lab (Speech Science Lab): “Speech Production Organs - Numbered” Theresa Knott / CC BY-SA 2.5 (cropped)
- Related lab (Speech Information Processing Lab): “Tracto vocal” Itsnaaav / CC BY-SA 4.0 (cropped)
- Related lab (Speech Information Processing Lab (Tokihiko Kaburagi)): “Petra, People in conversation, Jordan” Vyacheslav Argenberg / CC BY 4.0 (cropped)
- Related lab (Color and Vision Science Lab): “Color-palette-dynamic-color” Vijay Verma / CC0 (cropped)
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