The corpus contains recordings of male speaker, native in Czech, talking in English. The sentences that were read by the speaker originate in the domain of air traffic control (ATC), specifically the messages used by plane pilots during routine flight. The text in the corpus originates from the transcripts of the real recordings, part of which has been released in LINDAT/CLARIN (http://hdl.handle.net/11858/00-097C-0000-0001-CCA1-0), and individual phrases were selected by special algorithm described in Jůzová, M. and Tihelka, D.: Minimum Text Corpus Selection for Limited Domain Speech Synthesis (DOI 10.1007/978-3-319-10816-2_48). The corpus was used to create a limited domain speech synthesis system capable of simulating a pilot communication with an ATC officer.
The corpus contains recordings of male speaker, native in German, talking in English. The sentences that were read by the speaker originate in the domain of air traffic control (ATC), specifically the messages used by plane pilots during routine flight. The text in the corpus originates from the transcripts of the real recordings, part of which has been released in LINDAT/CLARIN (http://hdl.handle.net/11858/00-097C-0000-0001-CCA1-0), and individual phrases were selected by special algorithm described in Jůzová, M. and Tihelka, D.: Minimum Text Corpus Selection for Limited Domain Speech Synthesis (DOI 10.1007/978-3-319-10816-2_48). The corpus was used to create a limited domain speech synthesis system capable of simulating a pilot communication with an ATC officer.
The corpus contains recordings of male speaker, native in Serbian, talking in English. The sentences that were read by the speaker originate in the domain of air traffic control (ATC), specifically the messages used by plane pilots during routine flight. The text in the corpus originates from the transcripts of the real recordings, part of which has been released in LINDAT/CLARIN (http://hdl.handle.net/11858/00-097C-0000-0001-CCA1-0), and individual phrases were selected by special algorithm described in Jůzová, M. and Tihelka, D.: Minimum Text Corpus Selection for Limited Domain Speech Synthesis (DOI 10.1007/978-3-319-10816-2_48). The corpus was used to create a limited domain speech synthesis system capable of simulating a pilot communication with an ATC officer.
The corpus contains recordings of male speaker, native in Taiwanese, talking in English. The sentences that were read by the speaker originate in the domain of air traffic control (ATC), specifically the messages used by plane pilots during routine flight. The text in the corpus originates from the transcripts of the real recordings, part of which has been released in LINDAT/CLARIN (http://hdl.handle.net/11858/00-097C-0000-0001-CCA1-0), and individual phrases were selected by special algorithm described in Jůzová, M. and Tihelka, D.: Minimum Text Corpus Selection for Limited Domain Speech Synthesis (DOI 10.1007/978-3-319-10816-2_48). The corpus was used to create a limited domain speech synthesis system capable of simulating a pilot communication with an ATC officer.
ORAL2013 is designed as a representation of authentic spoken Czech used in informal situations (private environment, spontaneity, unpreparedness etc.) in the area of the whole Czech Republic. The corpus comprises 835 recordings from 2008–2011 that contain 2 785 189 words (i.e. 3 285 508 tokens including punctuation) uttered by 2 544 speakers, out of which 1 297 speakers are unique. ORAL2013 is balanced in the main sociolinguistic categories of the speakers (gender, age group, education, region of childhood residence).
The (anonymized) transcriptions are provided in the Transcriber XML format, audio (with corresponding anonymization beeps) is in uncompressed 16-bit PCM WAV, mono, 16 kHz format.
Another format option of the transcriptions is also available under less restrictive CC BY-NC-SA license at http://hdl.handle.net/11234/1-1847
The corpus consists of transcribed recordings from the Czech political discussion broadcast “Otázky Václava Moravce“. It contains 35 hours of speech and corresponding word-by-word transcriptions, including the transcription of some non-speech events. Speakers’ names are also assigned to corresponding segments. The resulting corpus is suitable for both acoustic model training for ASR purposes and training of speaker identification and/or verification systems. The archive contains 16 sound files (WAV PCM, 16-bit, 48 kHz, mono) and transcriptions in XML-based standard Transcriber format (http://trans.sourceforge.net)
The ParCzech 3.0 corpus is the third version of ParCzech consisting of stenographic protocols that record the Chamber of Deputies’ meetings held in the 7th term (2013-2017) and the current 8th term (2017-Mar 2021). The protocols are provided in their original HTML format, Parla-CLARIN TEI format, and the format suitable for Automatic Speech Recognition. The corpus is automatically enriched with the morphological, syntactic, and named-entity annotations using the procedures UDPipe 2 and NameTag 2. The audio files are aligned with the texts in the annotated TEI files.
The ParCzech 4.0 corpus consists of stenographic protocols that record the Chamber of Deputies' meetings in the 7th term (2013-2017), the 8th term (2017-2021) and the current 9th term (2021-Jul 2023). The protocols are provided in their original HTML format, Parla-CLARIN TEI format. The corpus is automatically enriched with the morphological, syntactic, and named-entity annotations using the procedures UDPipe 2 and NameTag 2. The audio files are aligned with the texts in the annotated TEI files.
The audio files in this corpus are available in AudioPSP 24.01 corpus (http://hdl.handle.net/11234/1-5404).
This corpus covers the same period as ParlaMint-CZ corpus v4.0 (http://hdl.handle.net/11356/1860). ParCzech corpus follows and extends the ParlaMint schema. Both annotated and non-annotated versions include hypertext references to voting and parliamentary prints. In addition to ParlaMint's recommendation, the annotated version contains source audio alignment, PDT xtag, and more detailed CNEC2.0 named entity categorization.
Studio recordings of spontaneous Estonian segmented phonetically on word, sound, and other linguistic levels. Current size about 22 hours of speech, 155 000 words. Online search engine lets you search from word-level segments and returns matching 2 second sequences of sound and segmentation.