Browsing School of Informatics by Title
Now showing items 24-43 of 87
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GitHub Java Corpus
The GitHub Java Corpus is a snapshot of all open-source Java code on GitHub in October 2012 that is contained in open-source projects that at the time had at least one fork. It contains code from 14,785 projects amounting ... -
Hiberlink project data
Summary files (in XML format) listing URIs referenced in papers from arXiv, Elsevier, and PMC respectively (approximately 1 million URIs from 3 million papers in total). The focus of the Hiberlink project was to assess the ... -
The Human Know-How Dataset
The Human Know-How Dataset describes 211,696 human activities from many different domains. These activities are decomposed into 2,609,236 entities (each with an English textual label). These entities represent over two ... -
Human vs Machine Spoofing
Listening test materials for "Human vs Machine Spoofing Detection on Wideband and Narrowband data." They include lists of the speech material selected from the SAS spoofing database and the listeners' responses. The main ... -
Hurricane natural speech corpus
(LISTA Consortium: (i) Language and Speech Laboratory, Universidad del Pais Vasco, Spain and Ikerbasque, Spain; (ii) Centre for Speech Technology Research, University of Edinburgh, UK; (iii) KTH Royal Institute of Technology, Sweden; (iv) Institute of Computer Science, FORTH, Greece, 2013-10-01)Single male native British-English talker recorded producing three speech sets (Harvard sentences, Modified Rhyme Test, news sentences) in quiet and while the talker was listening to speech-shaped noise at 84dB(A). A higher ... -
Hurricane natural speech corpus - higher quality version
Single male native British-English talker recorded producing three speech sets (Harvard sentences, Modified Rhyme Test, news sentences) in quiet and while the talker was listening to speech-shaped noise at 84dB(A). This ... -
IDEAL Household Energy Dataset
The IDEAL Household Energy Dataset comprises data from 255 UK homes. Alongside electric and gas data from each home the corpus contains individual room temperature and humidity readings and temperature readings from the ... -
Key files for Spoofing and Anti-Spoofing (SAS) corpus v1.0
These files are complementary to the fileset: Wu et al. (2015). Spoofing and Anti-Spoofing (SAS) corpus v1.0, [dataset]. University of Edinburgh. The Centre for Speech Technology Research (CSTR). https://doi.org/10.7488/ds/252. ... -
Listening test materials for "A study of speaker adaptation for DNN-based speech synthesis"
The dataset contains the testing stimuli and listeners' MUSHRA test responses for the Interspeech 2015 paper, "A study of speaker adaptation for DNN-based speech synthesis". In this paper, we conduct an experimental analysis ... -
Listening test materials for "A template-based approach for speech synthesis intonation generation using LSTMs"
This data release contains listening test materials associated with the paper "A template-based approach for speech synthesis intonation generation using LSTMs", presented at Interspeech 2016 in San Francisco, USA. -
Listening test materials for "Deep neural network context embeddings for model selection in rich-context HMM synthesis"
These are the listening test materials for "Deep neural network context embeddings for model selection in rich-context HMM synthesis". They include the waveforms played to listeners as well as the listeners' responses. -
Listening test materials for "Deep neural network-guided unit selection synthesis"
These are the listening test materials for "Deep neural network-guided unit selection synthesis". They include the waveforms played to listeners as well as the listeners' responses. -
Listening test materials for "Evaluating comprehension of natural and synthetic conversational speech"
Current speech synthesis methods typically operate on isolated sentences and lack convincing prosody when generating longer segments of speech. Similarly, prevailing TTS evaluation paradigms, such as intelligibility ... -
Listening test materials for "From HMMs to DNNs: Where do the improvements come from?"
This data release contains listening test materials associated with the paper "From HMMs to DNNs: Where do the improvements come from?", presented at ICASSP 2016 in Shanghai, China. -
Listening test materials for "Multiple Feed-forward Deep Neural Networks for Statistical Parametric Speech Synthesis"
In the paper which this data accompanies, we investigate a combination of several feed-forward deep neural networks (DNNs) for a high-quality statistical parametric speech synthesis system. Recently, DNNs have significantly ... -
Listening test materials for "Robust TTS duration modelling using DNNs"
This data release contains listening test materials associated with the paper "Robust TTS duration modelling using DNNs", presented at ICASSP 2016 in Shanghai, China. -
Listening test materials for "Smooth Talking: Articulatory Join Costs for Unit Selection"
This is the listening test data for the experiment presented in the ICASSP 2016 paper "Smooth Talking: Articulatory Join Costs for Unit Selection", which proposes and evaluates computation of unit selection join costs in ... -
Listening test materials for "Waveform generation based on signal reshaping for statistical parametric speech synthesis"
The dataset contains the testing stimuli and listeners' MUSHRA test responses for the Interspeech 2016 paper "Waveform generation based on signal reshaping for statistical parametric speech synthesis". On this paper, we ... -
Listening test results of the Voice Conversion Challenge 2018
This dataset is associated with a paper and a dataset below: (1) Jaime Lorenzo-Trueba, Junichi Yamagishi, Tomoki Toda, Daisuke Saito, Fernando Villavicencio, Tomi Kinnunen, Zhenhua Ling, "The Voice Conversion Challenge ... -
Listening-test materials for "Modern speech synthesis for phonetic sciences: a discussion and an evaluation"
This data release contains listening-test materials associated with the paper "Modern speech synthesis for phonetic sciences: a discussion and an evaluation", presented at ICPhS 2019 in Melbourne, Australia.
