Michelle Cohn

Education

• Ph.D. Linguistics (University of California, Davis)
• BA Linguistics & Italian Studies (University of California, Santa Barbara)

Website

For more news, more information about my research projects, and more, please see my website: michelledcohn.com

Research

My research program aims to uncover the cognitive mechanisms that underlie how people produce, perceive, and learn speech patterns with voice technology. In particular, I am interested in the flexibility of the speech system, such as the impact of top-down factors. These include examinations of real (or assumed) barriers (e.g., ASR listeners), perceptions of the social attributes of another talker (e.g., their human-likeness, emotional expressiveness), and individual variation (e.g., by age, cognitive characteristics).

1. Produce

Adapting speech for voice assistants / errors

• Cohn, M., Ferenc Segedin, B., & Zellou, G. (2022). The acoustic-phonetic properties of Siri- and human-DS: Differences by error type and rate. Journal of Phonetics. [OA Article]
• Cohn, M., & Zellou, G. (2021). Prosodic differences in human- and Alexa-directed speech, but similar error correction strategies. Frontiers in Communication. [OA Article]
• Cohn, M., Liang, K., Sarian, M., Zellou, G., & Yu, Z. (2021). Speech rate adjustments in conversations with an Amazon Alexa socialbot. Frontiers in Communication [OA Article]
• Cohn, M., Barreda, B., Graf Estes, K., Yu, Z., & Zellou, G. (in prep). Talking to technology: Children and adults produce distinct acoustic adjustments.
• Cohn, M., Pycha, A., & Zellou, G. (in prep). Real versus imagined addressees: Prosodic differences across human- and device-directed speech.

Face-masked speech

• Cohn, M., Pycha, A., & Zellou, G. (2021). Intelligibility of face-masked speech depends on speaking style: Comparing casual, smiled, and clear speech. Cognition [Article] [pdf]
• Cohn, M., Pycha, A., & Zellou (in prep). Children’s adaptations across face-masked and unmasked speech.

2. Perceive

Perceiving text-to-speech (TTS) voices

• Cohn, M. & Zellou, G. (2020). Perception of concatenative vs. Neural text-to-speech (TTS): Differences in intelligibility in noise and language attitudes. Interspeech [pdf] [Virtual Talk]
• Aoki, N., Cohn, M., & Zellou, G. (2022). The clear speech intelligibility benefit for text-to-speech voices: Effects of speaking style and visual guise. Journal of Acoustical Society of America (JASA) Express Letters. [OA Article]
• Cohn, M, Sarian, M., Predeck, K., & Zellou, G. (2020). Individual variation in language attitudes toward voice-AI: The role of listeners’ autistic-like traits. Interspeech [pdf] [Virtual talk]
• Snyder, C. Cohn, M., & Zellou, G. (2019). Individual variation in cognitive processing style predicts differences in phonetic imitation of device and human voices. Interspeech [pdf]

Perceiving face-masked speech

• Pycha, A., Cohn, M., & Zellou, G. (2022). Face-masked speech intelligibility: the influence of speaking style, visual information, and background noise. Frontiers in Communication. [OA Article]
• Zellou, G., Pycha, A., & Cohn, M. (2023). The perception of nasal coarticulatory variation in face-masked speech. The Journal of the Acoustical Society of America, 153(2), 1084-1093. [Article]

Responses to emotion from voice technology

• Cohn, M., Predeck, K., Sarian, M., & Zellou, G. (2021). Prosodic alignment toward emotionally expressive speech: Comparing human and Alexa model talkers. Speech Communication. [OA Article]
• Cohn, M., Raveh, E., Predeck, K., Gessinger, I., Möbius, B., & Zellou, G. (2020). Differences in Gradient Emotion Perception: Human vs. Alexa Voices. Interspeech [pdf] [Virtual talk]
• Cohn, M., & Zellou, G. (2019). Expressiveness influences human vocal alignment toward voice-AI. Interspeech [pdf]
• Cohn, M., Chen, C., & Yu, Z. (2019). A Large-Scale User Study of an Alexa Prize Chatbot: Effect of TTS Dynamism on Perceived Quality of Social Dialog. SIGDial [pdf]
• Gessinger, I., Cohn, M., Möbius, B., & Zellou, G (2022). Cross-Cultural Comparison of Gradient Emotion Perception: Human vs. Alexa TTS Voices. Interspeech [pdf].
• Zhu, Q., Chau, A., Cohn, M., Liang, K-H, Wang, H-C, Zellou, G., & Yu, Z. (2022). Effects of Emotional Expressiveness on Voice Chatbot Interactions. 4th Conference on Conversational User Interfaces (CUI). [pdf]

Perception of phonetic detail in human-human interaction

• Cohn, M., Barreda, S., & Zellou, G. (2023) Differences in a musician’s advantage for speech-in-speech perception based on age and task. Journal of Speech Language, and Hearing Research. [Article] [pdf]
• Cohn, M., Zellou, G., & Barreda, S. (2019). The role of musical experience in the perceptual weighting of acoustic cues for the obstruent coda voicing contrast in American English. Interspeech [pdf]
• Zellou, G., Cohn, M., & Block, A. (2021). Partial compensation for coarticulatory vowel nasalization across concatenative and neural text-to-speech. Journal of the Acoustic Society of America [Article]
• Block, A., Cohn, M., & Zellou, G. (2021). Variation in Perceptual Sensitivity and Compensation for Coarticulation Across Adult and Child Naturally-produced and TTS Voices. Interspeech. [pdf]

3. Learn

Learn a novel pattern

• Zellou, G., Cohn, M., & Pycha, A. (accepted). The effect of listener beliefs on perceptual learning. Language.
• Cohn, M., Graf Estes, K., & Zellou, G. (in prep). Learning lexical tone from concatenative and neural text-to-speech (TTS) voices.
• Ferenc Segedin, B. Cohn, M., & Zellou, G. (2019). Perceptual adaptation to device and human voices:  learning and generalization of a phonetic shift across real and voice-AI talkers. Interspeech [pdf]

Mirror/align/imitate another speakers’ patterns

• Cohn, M., Keaton, K., Beskow, J., & Zellou, G. (2023). Vocal accommodation to technology: The role of physical form. Language Sciences 99, 101567. [OA Article]
• Cohn, M., Ferenc Segedin, B., & Zellou, G. (2019). Imitating Siri: Socially-mediated vocal alignment to device and human voices. ICPhS [pdf]
• Cohn, M., Jonell, P., Kim, T., Beskow, J., & Zellou, G. (2020). Embodiment and gender interact in alignment to TTS voices. Cognitive Science Society [OA Article] [Virtual talk]
• Dodd, N., Cohn, M., & Zellou, G. (2023). Comparing alignment toward American, British, and Indian English text-to-speech (TTS) voices: Influence of social attitudes and talker guise. Frontiers in Computer Science, 5. [Article]
• Zellou, G., Cohn, M., & Ferenc Segedin, B. (2021). Age- and gender-related differences in speech alignment toward humans and voice-AI. Frontiers in Communication [OA Article]
• Zellou, G., Cohn, M., & Kline, T. (2021). The Influence of Conversational Role on Phonetic Alignment toward Voice-AI and Human Interlocutors. Language, Cognition and Neuroscience [Article][pdf]
• Zellou, G., & Cohn, M. (2020). Top-down effects of apparent humanness on vocal alignment toward human and device interlocutors. Cognitive Science Society [pdf]

Teaching

• Associate Instructor (LIN 1, 103a)
• Teaching Assistant (LIN 1, 1Y, 106, 103a, 103b, 111, 151, 152; COM 1)
• Reader (LIN 111)

Awards

• Award for Excellence in Postdoctoral Research. UC Davis Graduate Studies and
  UC Davis Postdoctoral Scholars Association (PSA)
• Honorable Mention, Chancellor's Award for Excellence in Mentoring Undergraduate
  Research (postdoc/project scientist category). UC Davis Undergraduate Research Center
• Outstanding Graduate Student Teaching Award, UC Davis
• Finalist, 5 Minute Linguist Competition. Linguistic Society of America Annual Meeting
• Finalist for Most Innovative Research Award. UC Davis Language Symposium
• Lapointe Award, Department of Linguistics, UC Davis
• Chancellor’s Prize for Best Oral Presentation, Interdisciplinary Graduate & Professional Symposium, UC Davis
• Best Oral Presentation in Social Sciences, Interdisciplinary Graduate & Professional Symposium, UC Davis