This paper describes the development of the Wildcat Corpus of native- and foreign-accented English,a corpus containing scripted and spontaneous speech recordings from 24 native speakers of American English and 52 non-native speakers of English.The core element of this corpus is a set of spontaneous speech recordings, for which a new method of eliciting dialogue-based, laboratory-quality speech recordings was developed (the Diapix task). Dialogues between two native speakers of English, between two non-native speakers of English (with either shared or different LIs), and between one native and one non-native speaker of English are included and analyzed in terms of general measures of communicative efficiency.The overall finding was that pairs of native talkers were most efficient, followed by mixed native/non-native pairs and non-native pairs with shared LI. Non-native pairs with different LIs were least efficient.These results support the hypothesis that successful speech communication depends both on the alignment of talkers to the target language and on the alignment of talkers to one another in terms of native language background.
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http://dx.doi.org/10.1177/0023830910372495 | DOI Listing |
Imaging Neurosci (Camb)
April 2024
Department of Electrical Engineering, Columbia University, New York, NY, United States.
Listeners with hearing loss have trouble following a conversation in multitalker environments. While modern hearing aids can generally amplify speech, these devices are unable to tune into a target speaker without first knowing to which speaker a user aims to attend. Brain-controlled hearing aids have been proposed using auditory attention decoding (AAD) methods, but current methods use the same model to compare the speech stimulus and neural response, regardless of the dynamic overlap between talkers which is known to influence neural encoding.
View Article and Find Full Text PDFTelehealth is increasing popular as a treatment option for people with Parkinson disease (PD). The SpeechVive device is a wearable device that uses the Lombard effect to help patients speak more loudly, slowly, and clearly. This study sought to examine the effectiveness of the device to improve communication in people with PD, delivered over a telehealth modality as compared to in-person, using implementation science design.
View Article and Find Full Text PDFACM Trans Access Comput
December 2024
University of California, Santa Cruz, 1156 High Street, Santa Cruz, California, USA.
We describe two iOS apps designed to support blind travelers navigating in indoor building environments. The Wayfinding app provides guidance to a blind user while following a certain route. The Backtracking app records the route taken by the walker towards a certain destination, then provides guidance while re-tracing the same trajectory in the opposite direction.
View Article and Find Full Text PDFIn this paper, we present StyleTTS 2, a text-to-speech (TTS) model that leverages style diffusion and adversarial training with large speech language models (SLMs) to achieve human-level TTS synthesis. StyleTTS 2 differs from its predecessor by modeling styles as a latent random variable through diffusion models to generate the most suitable style for the text without requiring reference speech, achieving efficient latent diffusion while benefiting from the diverse speech synthesis offered by diffusion models. Furthermore, we employ large pre-trained SLMs, such as WavLM, as discriminators with our novel differentiable duration modeling for end-to-end training, resulting in improved speech naturalness.
View Article and Find Full Text PDFOtolaryngol Head Neck Surg
January 2025
Department of Otolaryngology-Head and Neck Surgery, Columbia University Vagelos College of Physicians and Surgeons, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, New York, USA.
Objective: Hearing loss (HL) is associated with depression, but existing datasets are limited by the type of data available for both hearing and mental health conditions. The purpose of this study is to determine if there is an association between HL and depressive disorders within a large bi-institutional electronic health record (EHR) system containing more granular diagnostic information.
Study Design: Cross-sectional epidemiologic study.
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