Model-Matched Sounds

Cochleograms and sound files are shown for example stimuli from the model-matching experiment.

Authors:  Sam V. Norman-Haignere & Josh H. McDermott
Updated:  2018-12-03
Source:  http://mcdermottlab.mit.edu/svnh/model-matching/Stimuli_from_Model-Matching_Experiment.html
Keywords:  audition,  sensory,  auditory-cortex,  neuroscience,  English

Inharmonic Speech Segregation

Inharmonic speech demos showing sound segregation.

Authors:  Sara Popham,  Dana Boebinger,  Dan P. W. Ellis,  Hideki Kawahara,  Josh H. McDermott
Updated:  2018-05-29
Source:  http://mcdermottlab.mit.edu/inharmonic_speech_examples/index.html
Keywords:  sound-sources,  brain,  frequency,  harmonics,  English

Texture-Time Averaging

Audio files showing the adaptive and selective time-averaging of auditory scenes.

Authors:  Richard McWalter & Josh McDermott
Updated:  2018-05-07
Source:  http://mcdermottlab.mit.edu/textint.html
Keywords:  perception,  sensory-input,  audition

SNAFU: the Semantic Network and Fluency Utility

A set of resources for analyzing fluency data

Authors:  Jeffrey C. Zemla & Joseph L. Austerweil
Updated:  2018-04-30
Source:  https://github.com/AusterweilLab/snafu-py
Keywords:  linguistics,  semantics,  experimentation,  age of acquisition,  fluency

Phonotactic Probability Calculator

Used to calculate the phonotactic probabilities of real English, Arabic, and Spanish words or specially constructed nonwords. Analyses can be performed on words or nonwords up to 17 phonemes in length.

Authors:  Michael Vitevitch
Updated:  2018-04-30
Source:  https://calculator.ku.edu/phonotactic/about
Keywords:  phonotactic-probability,  psychology,  phonetics,  language-processing,  Arabic,  English,  Spanish

Schema Learning for the Cocktail Party Problem

The cocktail party problem requires listeners to infer individual sound

Authors:  Kevin J.P. Woods & Josh H. McDermott
Updated:  2018-04-03
Source:  http://mcdermottlab.mit.edu/schema_learning/index.html
Keywords:  sound-sources,  audition,  schema

Combinatorial Expressive Speech Engine

C.L.E.E.S.E. (Combinatorial Expressive Speech Engine) is a tool designed to generate an infinite number of natural-sounding, expressive variations around an original speech recording.

Authors:  Juan José Burred,  Emmanuel Ponsot
Updated:  2018-03-30
Source:  http://cream.ircam.fr/?p=521
Keywords:  language,  speech,  pitch,  French,  English,  Japanese

ANGUS

ANGUS is a real-time voice transformation tool able to simulate cues of arousal/roughness on arbitrary voice signals with a high degree of realism.

Authors:  Marco Liuni,  Luc Ardaillon
Updated:  2018-03-07
Source:  http://cream.ircam.fr/?p=787
Keywords:  language,  voice,  vocal-tract,  English

Tool for the Automatic Analysis of Lexical Sophistication

TAALES is a tool that measures over 400 classic and new indices of lexical sophistication, and includes indices related to a wide range of sub-constructs.

Authors:  Kristopher Kyle,  Scott Crossley,  Cynthia Berger
Updated:  2018-02-08
Source:  https://www.linguisticanalysistools.org/taales.html
Keywords:  language,  lexicon,  communication,  English

Time Invariant String Kernel Model

TISK is the Time Invariant String Model of (human) spoken word recognition.

Authors:  Heejo You,  Thomas Hannagan,  James Magnuson
Updated:  2017-12-15
Source:  https://github.com/maglab-uconn/TISK1.0
Keywords:  word-recognition,  phonetics,  python,  English