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Speech recognition, text-to-speech, speaker identification, music classification, audio event detection
2,024 datasets
Laying out neural firing rate evidence from a rodent model (Meriones unguiculatus) investigating midbrain adaptation's role in musical beat perception. It compares on-beat and off-beat sound responses, with findings suggesting basic firing rate adaptation shapes perceptual emergence. Specific row and column counts are unavailable.
A 2020 dataset from Piotr Łukasik investigates the effects of facultative endosymbiotic bacteria on aphid hosts. It measures aphid fecundity and susceptibility to an entomopathogenic fungus across multiple host genotypes and species, with symbionts transferred either together or separately. The study explores how protective phenotypes conferred by Rickettsia and Spiroplasma vary among host backgrounds and are influenced by co-infection with Hamiltonella.
A collection of symbolic music datasets curated for Music Information Retrieval research. The datasets were last updated in June 2020 by author wayne391.
5,358 audio tracks featuring synchronized lyrics and vocal notes across multiple languages and genres. The dataset provides hierarchical alignments at the paragraph, line, word, and character levels, paired with fundamental frequency (F0) information for the singing voice.
February 6-9, 2020 data collected with a 1GHz ground penetrating radar during the SnowEx 2020 Intensive Observation Period at Grand Mesa, Colorado. It contains derived measurements of two-way travel times, snow depth, and snow water equivalent. The data set is provided by NSIDC_CPRD.
10 single-speaker speech datasets covering 10 languages including German, Greek, Spanish, Finnish, French, Hungarian, Japanese, Dutch, Russian, and Chinese. Each language-specific subset contains audio recordings paired with text transcriptions for speech synthesis tasks.
The Var department in France contains a dataset classifying railway land transport infrastructure by noise levels, based on a prefectural decree from September 29, 2016. It likely contains polygons or zones representing areas affected by noise, categorized from 1 (noisiest) to 5, with defined nuisance sector widths. The dataset was produced by the Bureau de Recherches Géologiques et Minières (BRGM) and was last updated on January 10, 2020.
Multiple audio datasets are supported through this collection of specialized PyTorch and TensorFlow data loading scripts. The repository provides the necessary infrastructure to convert raw audio signals into framework-ready tensors for deep learning research.
Physical trajectory profile data was collected by a University of Massachusetts - Dartmouth glider during a 90-day mission from August to September 2019. The dataset contains measurements of oceanographic properties like temperature, salinity, and chlorophyll a to investigate Mid-Atlantic Cold Pool dynamics. The data was assembled by the IOOS National Glider Data Assembly Center and archived by NOAA's National Centers for Environmental Information.
Approved by Prefectural Order No. 75-2019-10-03-003 on 3 October 2019, this dataset contains the sound classification of RATP railway infrastructure in the Paris department. It segments overhead railway lines into homogeneous sections and assigns them a noise category from 1 to 5, where a higher number indicates a lower assumed noise level at the infrastructure edge. The data is provided by the Bureau de Recherches Géologiques et Minières (BRGM) and was last updated on 7 October 2019.
A 2016 noise classification for land transport infrastructure in France's Sarthe department, approved by a prefectural decree on March 18, 2016. It categorizes roads, railways, and public transport lanes based on generated noise levels to determine zones requiring reinforced building insulation. The dataset was produced by the Bureau de Recherches Géologiques et Minières and last updated in April 2019.
497 solo piano pieces comprising synchronized sheet music images, MIDI files, and synthesized audio recordings. The dataset provides precise note-level alignments across visual and auditory modalities for classical music compositions.
The European Directive 2002/49/EC mandates a harmonised assessment of environmental noise exposure. This dataset contains strategic noise maps for type B land transport infrastructure in the Meurthe-et-Moselle department of France, produced by CEREMA and aggregated using the QGIS MIZOGEO plugin. The maps were last updated on April 5, 2019.
The Nuisance — Meurthe-et-Moselle Land Transport Infrastructure Layer of Type B Strategic Noise Maps dataset was created by the Bureau de Recherches Géologiques et Minières (BRGM) and sourced from CEREMA. It contains strategic noise maps produced under the European Directive 2002/49/EC, representing sectors affected by noise for assessment and urban planning purposes. The data was last updated on April 5, 2019.
A census and classification of road infrastructure based on noise and traffic characteristics, covering the average daily traffic network of more than five thousand vehicles. The dataset is published by the Prefect of the department of Seine-et-Marne and was last updated in April 2019. Classification references sound levels defined by French interministerial decrees from 1996 and 2013.
August 6 to October 21, 2018 data from a glider mission measuring physical oceanographic properties in the Mid-Atlantic Bight. The dataset contains measurements from glider BLUE deployed by the University of Massachusetts - Dartmouth, focusing on seasonal-varying features of the Mid-Atlantic Cold Pool. It was archived by NOAA's National Centers for Environmental Information.
Six months of field sampling and orthographic image analysis in 2018 documented ice-rafted sediment deposits in the Great Marsh, Massachusetts. The dataset, curated by NOAA's National Centers for Environmental Information, includes deposit locations, thickness measurements, and calculated total sediment coverage. Data is stored in an ArcGIS geodatabase with shapefiles and supporting Excel spreadsheets.
September 2017 data from a NOAA Okeanos Explorer expedition focused on the Musicians Seamounts in the Pacific Ocean. It includes oceanographic, meteorological, and navigation data collected via 24-hour operations using ROVs, mapping systems, and telepresence. The dataset was compiled by NOAA's National Centers for Environmental Information.
August 31 to September 22, 2017 trajectory data from the glider 'Blue' deployed by the University of Massachusetts - Dartmouth. The dataset contains physical oceanographic measurements like temperature, salinity, conductivity, density, chlorophyll, backscatter, CDOM, and oxygen. It was collected as part of the 'Investigation of Mid-Atlantic Cold Pool Dynamics' program and archived by NOAA's National Centers for Environmental Information.
Multiple speech corpora across Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) categories. These resources provide audio recordings and text transcriptions for speech-related machine learning tasks.