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These transcripts and video files are samples of Spanish and English caregiver (almost always mother)-child interaction collected at child ages 2 ½, 3, and 3 ½ years as part of a 10-year longitudinal study of the language and literacy development of U.S.-born children raised in Spanish-speaking homes. Each recording is approximately 30 minutes in length. The caregiver and target child are...
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The MSP-Podcast corpus contains speech segments from podcast recordings which are perceptually annotated using crowdsourcing. The collection of this corpus is an ongoing process. Version 1.11 of the corpus has 151,654 speaking turns (237 hours and 56 mins). The proposed partition attempts to create speaker-independent datasets for Train, Development, Test1, Test2, and Test3 sets.
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The British National Corpus (BNC) is a 100 million word collection of samples of written and spoken language from a wide range of sources, designed to represent a wide cross-section of British English, both spoken and written, from the late twentieth century. Access the data here: https://llds.ling-phil.ox.ac.uk/llds/xmlui/handle/20.500.14106/2554
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A sound vocabulary and dataset AudioSet consists of an expanding ontology of 632 audio event classes and a collection of 2,084,320 human-labeled 10-second sound clips drawn from YouTube videos. The ontology is specified as a hierarchical graph of event categories, covering a wide range of human and animal sounds, musical instruments and genres, and common everyday environmental sounds. By...
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This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech accent archive.
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VoxForge is an open speech dataset that was set up to collect transcribed speech for use with Free and Open Source Speech Recognition Engines (on Linux, Windows and Mac).
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Common Voice is a project to help make voice recognition open to everyone. Developers need an enormous amount of voice data to build voice recognition technologies, and currently most of that data is expensive and proprietary. We want to make voice data freely and publicly available, and make sure the data represents the diversity of real people. Together we can make voice recognition better for everyone.
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