In This post we share top Datasets for Speech Recognition. Speech emotion analysis is an important task which further enables several application use cases. Due to the widespread use of smartphones,
In This post we share top Datasets for Speech Recognition. Speech emotion analysis is an important task which further enables several application use cases. Due to the widespread use of smartphones, it becomes viable to analyze speech commands captured using microphones for emotion understanding by utilizing on-device machine learning models
Google Audio Dataset is a large-scale dataset of manually annotated audio events. In this Daataset 2.1 million annotated videos, 5.8 thousand hours of audio with 527 classes of annotated sounds.
Some Audio Classes are given below
This is Urbansound Dataset. This dataset contains 1302 labeled sound recordings. Each recording is labeled with the start and end times of sound events from 10 classes: air_conditioner, car_horn, children_playing, dog_bark, drilling, enginge_idling, gun_shot, jackhammer, siren, and street_music. Each recording may contain multiple sound events, but for each file only events from a single class are labeled.
This dataset in Both CSV and JSON File. You can Download and Grow your Machine Learning Skills.
This is simple audio/speech dataset consisting of recordings of spoken digits in wav files at 8kHz. The recordings are trimmed so that they have near minimal silence at the beginnings and ends. FSDD is open Dataset for Everyone. In this Dataset 4 Speakers with 2000 Recordings in English pronunciations.
No. of Rows:- 2000
Detecting bird sounds in audio is an important task for automatic wildlife monitoring, as well as in citizen science and audio library management.you can download dataset through { freefield1010: • [data labels] • [audio files (5.8 Gb zip)] (or [via bittorrent]) Warblr: • [data labels] • [audio files (4.3 Gb zip)] (or [via bittorrent]) }
Can you build an algorithm that understands simple speech commands? If Yes than this Dataset is for you. Note: There are only 12 possible labels for the Test set: yes, no, up, down, left, right, on, off, stop, go, silence, unknown. The unknown label should be used for a command that is not one one of the first 10 labels or that is not silence.
EmoSpeech Dataset India's first keyword-emotion dataset. Surveillance 3 datasets in one 8K Environment Samples, 8K Keywords Samples and 8K Emotion Samples.
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