#Tongue note recorder full
#Tongue note recorder professional
#Tongue note recorder download

To download the TaL1 dataset, you can run: rsync -av .ac.uk::tal-corpus/TaL1. Check the download instructions for the Ultrasuite repository to download subsets of the data. Warning: the commands below will download 49GB and 498GB of data, respectively! Please make sure you have enough disk space. However, note that we replace .ac.uk::ultrasuite with .ac.uk::tal-corpus. The instrutions are applicable to the TaL corpus, in case you prefer to download part of the data (an utterance, a specific data type, etc). To download the TaL corpus, please check the download instructions for the Ultrasuite repository.

#Tongue note recorder full

If you prefer to browse some samples before downloading the full data, you can download the samples directories. The datasets are quite large, so please make sure that you have enough disk space before attempting to download. These sample videos are also available online: In samples/video, there are a few video examples generated with the tal-tools visualiser. The core directory contains the core data for the dataset. The doc directory contains the documentation for the data, as well as some additional documents, such as version number and anonymised participant information. The directory samples/core provides a subset of the core data types and the directory samples/video provides video samples generated with the tal-tools visualiser. If you wish to have a quick look at the TaL corpus, you can download this directory first and browse some examples. The samples directory contains a subset of the larger dataset (2 samples per speaker/session). Users should be aware of this if using both datasets, particularly when designing training and test splits. Most prompts read in TaL1 were recorded by the first speakers in TaL80, but a small subset was read by all speakers. There is an overlap in the recorded prompts in the two datasets. For this reason, shared prompts are only marked within datasets (across speakers for TaL80 and sessions for TaL1). TaL1 and TaL80 follow a similar structure, but they are independent datasets. This file is identified by the extension. This annotation is available as a CSV file with start and end time in seconds of the short segments nd their respective transcription. The five core data types for this utterance are the files: 002_cal.txt, 002_cal.wav, 002_cal.sync, 002_cal.ult, 002_cal.param, 002_cal.mp3.īecause spontaneous speech utterances can be long in duration (up to 60 seconds), we manually annotated the boundaries of shorter time segments (typically 5-10 seconds). The second utterance recorded by speaker 01fi is a calibration utterance with the identifier 002_cal. Video images of the lips (synchronised to waveform)Įxample. Raw ultrasound data (.ult) and ultrasound parameters (.param) Text file with prompt and datetime of recording Data typesĮach utterance consists of five core data types, which can be identified by their file extension. The tag x denotes prompts that were shared across speakers (TaL80) or recording sessions (TaL1).Įxamples: 001_swa, 002_cal, 004_xaud, 028_spo, 029_xsil, 038_sil. Shared whispered speech utterance (TaL1 only)Ĭalibration prompts ( cal) and swallows ( swa) were read at the beginning and end of each recording session and before and after a short break. Spontaneous speech utterance (unprompted speech) Each file ID also includes a tag indicating the prompt type. See the prompt text file for recording date/time. File identifiersįor each speaker (TaL80) or session (TaL1), utterances are indexed according to their recording times. Instead, we have recording sessions, which are simply called day1, day2, da圓. The TaL1 dataset only has 1 speaker, so there are no speaker identifiers. Country identifiers are: (e)ngland, (s)cotland, (i)reland, (n)orthern-ireland, (o)ther. In the TaL80 dataset, speaker identifiers denote speaker number, gender (m/f), and country of origin. Each speaker was recording over a single recording session.

TaL80 is a multi-speaker dataset contains recording sessions of 81 native speakers of English without voice talent experience.

#Tongue note recorder professional

TaL1 is a single-speaker dataset containing data of one professional voice talent, a male native speaker of English, over six recording sessions.This corpus contains synchronised imaging data of extraoral (lips) and intraoral (tongue) articulators from 82 native speakers of English.įor more information, please read the TaL corpus paper here! The Tongue and Lips (TaL) corpus is a multi-speaker corpus of ultrasound images of the tongue and video images of lips. A multi-speaker corpus of ultrasound images of the tongue and video images of the lips