Search Results - "Cohn, Michelle"

Apparent-time variation in the use of multiple cues for perception of anticipatory nasal coarticulation in California English by Zellou, Georgia, Cohn, Michelle

“…This study examines apparent-time variation in the use of multiple acoustic cues present on coarticulatorily nasalized vowels in California English…”
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Prosodic Differences in Human- and Alexa-Directed Speech, but Similar Local Intelligibility Adjustments by Cohn, Michelle, Zellou, Georgia

“…The current study tests whether individuals ( n = 53) produce distinct speech adaptations during pre-scripted spoken interactions with a voice-AI assistant…”
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Children and adults produce distinct technology- and human-directed speech by Cohn, Michelle, Barreda, Santiago, Graf Estes, Katharine, Yu, Zhou, Zellou, Georgia

“…This study compares how English-speaking adults and children from the United States adapt their speech when talking to a real person and a smart speaker…”
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Face-Masked Speech Intelligibility: The Influence of Speaking Style, Visual Information, and Background Noise by Pycha, Anne, Cohn, Michelle, Zellou, Georgia

“…The current study investigates the intelligibility of face-masked speech while manipulating speaking style, presence of visual information about the speaker,…”
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Age- and Gender-Related Differences in Speech Alignment Toward Humans and Voice-AI by Zellou, Georgia, Cohn, Michelle, Ferenc Segedin, Bruno

“…Speech alignment is where talkers subconsciously adopt the speech and language patterns of their interlocutor. Nowadays, people of all ages are speaking with…”
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Comparing alignment toward American, British, and Indian English text-to-speech (TTS) voices: influence of social attitudes and talker guise by Dodd, Nicole, Cohn, Michelle, Zellou, Georgia

“…Text-to-speech (TTS) voices, which vary in their apparent native language and dialect, are increasingly widespread. In this paper, we test how speakers…”
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Linguistic patterning of laughter in human-socialbot interactions by Perkins Booker, Nynaeve, Cohn, Michelle, Zellou, Georgia

“…Laughter is a social behavior that conveys a variety of emotional states and is also intricately intertwined with linguistic communication. As people…”
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Speech Rate Adjustments in Conversations With an Amazon Alexa Socialbot by Cohn, Michelle, Liang, Kai-Hui, Sarian, Melina, Zellou, Georgia, Yu, Zhou

“…This paper investigates users’ speech rate adjustments during conversations with an Amazon Alexa socialbot in response to situational (in-lab vs. at-home) and…”
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Clear speech in the new digital era: Speaking and listening clearly to voice-AI systems by Zellou, Georgia, Cohn, Michelle

“…It’s a new digital era: many people regularly talk to voice-activated artificially intelligent (AI) personal assistants, such as Siri, Alexa, and Google…”
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Intelligibility of face-masked speech depends on speaking style: Comparing casual, clear, and emotional speech by Cohn, Michelle, Pycha, Anne, Zellou, Georgia

“…This study investigates the impact of wearing a fabric face mask on speech comprehension, an underexplored topic that can inform theories of speech production…”
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Acoustic-phonetic properties of Siri- and human-directed speech by Cohn, Michelle, Segedin, Bruno Ferenc, Zellou, Georgia

“…•Measured acoustic properties of speech produced to Siri vs. a human.•Siri-DS tends to be louder, has a lower mean f0, and a smaller f0 range.•Targeted vowel…”
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The perception of nasal coarticulatory variation in face-masked speech by Zellou, Georgia, Pycha, Anne, Cohn, Michelle

“…This study investigates the impact of wearing a face mask on the production and perception of coarticulatory vowel nasalization. Speakers produced monosyllabic…”
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Selective tuning of nasal coarticulation and hyperarticulation across slow-clear, casual, and fast-clear speech styles by Cohn, Michelle, Zellou, Georgia

“…This study investigates how California English speakers adjust nasal coarticulation and hyperarticulation on vowels across three speech styles: speaking slowly…”
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Partial compensation for coarticulatory vowel nasalization across concatenative and neural text-to-speech by Zellou, Georgia, Cohn, Michelle, Block, Aleese

“…This study investigates the perception of coarticulatory vowel nasality generated using different text-to-speech (TTS) methods in American English. Experiment…”
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Differences in a Musician's Advantage for Speech-in-Speech Perception Based on Age and Task by Cohn, Michelle, Barreda, Santiago, Zellou, Georgia

“…Purpose: This study investigates the debate that musicians have an advantage in speech-in-noise perception from years of targeted auditory training. We also…”
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Marking prosodic prominence for voice assistant and human addressees by Beier, Eleonora, Cohn, Michelle, Trammel, Timothy, Ferreira, Fernanda, Zellou, Georgia

“…Prosodic prominence (realized with phonetic features such as increased intensity, duration, and pitch, among others) is thought to guide listeners’ attention…”
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The influence of conversational role on phonetic alignment toward voice-AI and human interlocutors by Zellou, Georgia, Cohn, Michelle, Kline, Tyler

“…Two studies investigated the influence of conversational role on phonetic imitation toward human and voice-AI interlocutors. In a Word List Task, the giver…”
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Prosodic alignment toward emotionally expressive speech: Comparing human and Alexa model talkers by Cohn, Michelle, Predeck, Kristin, Sarian, Melina, Zellou, Georgia

“…•Participants shadow emotionally expressive and neutral productions•Comparison of speech toward human and Amazon Alexa model talkers•Evidence of alignment…”
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Comparing perception of L1 and L2 English by human listeners and machines: Effect of interlocutor adaptationsa by Vonessen, Jules, Aoki, Nicholas B., Cohn, Michelle, Zellou, Georgia

“…Speakers tailor their speech to different types of interlocutors. For example, speech directed to voice technology has different acoustic-phonetic…”
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Comparing perception of L1 and L2 English by human listeners and machines: Effect of interlocutor adaptations by Vonessen, Jules, Aoki, Nicholas B., Cohn, Michelle, Zellou, Georgia

“…Speakers tailor their speech to different types of interlocutors. For example, speech directed to voice technology has different acoustic-phonetic…”
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