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Ewald Enzinger's Projects

alias-free-torch icon alias-free-torch

Simple torch.nn.module implementation of Alias-Free-GAN style filter and resample

alice icon alice

Automatic LInguistic Unit Count Estimator (ALICE)

aligners icon aligners

HMM, CTC, RNN-Transducer, forward-backward algorithm

allosaurus icon allosaurus

Pretrained model for ICASSP 2020 "Universal Phone Recognition with a Multilingual Allophone System"

alm icon alm

Smart Language Model

alphapose icon alphapose

Real-Time and Accurate Multi-Person Pose Estimation&Tracking System

am-mobilenet1d icon am-mobilenet1d

The Additive Margin MobileNet1D is a new light weight deep learning model for Speaker Recognition which is based on the MobileNetV2 architecture and the Additive Margin Softmax (AM-Softmax) loss function.)

amepd icon amepd

American English Pronunciation Dictionary

amfm_decompy icon amfm_decompy

Package containing the tools necessary for decomposing a speech signal into its modulated components (also known as AM-FM decomposition). Includes the algorithms of the QHM family and the YAAPT pitch tracker.

amr-ie icon amr-ie

The code repository for AMR guided joint information extraction model (NAACL-2021).

amtl-bnfs-i-vector-based-lr icon amtl-bnfs-i-vector-based-lr

This is the implementation of an unpublished paper: Adversarial Multi-task deep feature and unsupervised back-end adpatation for language recognition

annyang icon annyang

:speech_balloon: Speech recognition for your site

anserini icon anserini

A toolkit for reproducible information retrieval research built on Lucene

anti-spoofing icon anti-spoofing

3 neural network spoofed speech countermeasures for detecting whether a speech sample is replayed or genuine.

armspeech icon armspeech

Autoregressive probabilistic modelling for speech synthesis.

asr-demo icon asr-demo

Interactive speech recognition demo using the local microphone

asr-hybrid-decoding icon asr-hybrid-decoding

This is an extension of kaldi speech recognition software which allows to perform decoding of speech with hybrid word and phoneme graphs. The output is a mix of in-vocabulary words and phoneme sequences. This decoding is suitable for systems with only a small dictionary available and for further recovery of OOV words.

asr24 icon asr24

24-hour Automatic Speech Recognition

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