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Found 18 papers, 5 papers with code
Developing Acoustic Models for Automatic Speech Recognition in Swedish
This is done employing hidden Markov models and using the SpeechDat database to train their parameters.
Dynamic Behaviour of Connectionist Speech Recognition with Strong Latency Constraints
This paper describes the use of connectionist techniques in phonetic speech recognition with strong latency constraints.
Segment Boundary Detection via Class Entropy Measurements in Connectionist Phoneme Recognition
The advantage of this measure is its simplicity as the posterior probabilities of each class are available in connectionist phoneme recognition.
S-HR-VQVAE: Sequential Hierarchical Residual Learning Vector Quantized Variational Autoencoder for Video Prediction
We address the video prediction task by putting forth a novel model that combines (i) our recently proposed hierarchical residual vector quantized variational autoencoder (HR-VQVAE), and (ii) a novel spatiotemporal PixelCNN (ST-PixelCNN).
Hierarchical Residual Learning Based Vector Quantized Variational Autoencoder for Image Reconstruction and Generation
We propose a multi-layer variational autoencoder method, we call HR-VQVAE, that learns hierarchical discrete representations of the data.
NAAQA: A Neural Architecture for Acoustic Question Answering
We also test the addition of a MALiMo module in our model on both CLEAR2 and DAQA.
STEP-GAN: A Step-by-Step Training for Multi Generator GANs with application to Cyber Security in Power Systems
In this study, we introduce a novel unsupervised countermeasure for smart grid power systems, based on generative adversarial networks (GANs).
From Visual to Acoustic Question Answering
The AQA task consists of analyzing an acoustic scene composed by a combination of elementary sounds and answering questions that relate the position and properties of these sounds.
Beyond the Self: Using Grounded Affordances to Interpret and Describe Others' Actions
It then uses this information to learn a mapping between its own actions and those performed by a human in a shared environment.
CLEAR: A Dataset for Compositional Language and Elementary Acoustic Reasoning
We introduce the task of acoustic question answering (AQA) in the area of acoustic reasoning.
Active Mini-Batch Sampling using Repulsive Point Processes
We first show that the phenomenon of variance reduction by diversified sampling generalizes in particular to non-stationary point processes.
Language Bootstrapping: Learning Word Meanings From Perception-Action Association
The model is based on an affordance network, i. e., a mapping between robot actions, robot perceptions, and the perceived effects of these actions upon objects.
Interactive Robot Learning of Gestures, Language and Affordances
A growing field in robotics and Artificial Intelligence (AI) research is human-robot collaboration, whose target is to enable effective teamwork between humans and robots.
Self-Supervised Vision-Based Detection of the Active Speaker as Support for Socially-Aware Language Acquisition
Active speaker detection is a fundamental prerequisite for any artificial cognitive system attempting to acquire language in social settings.
Semi-supervised Learning with Sparse Autoencoders in Phone Classification
We propose the application of a semi-supervised learning method to improve the performance of acoustic modelling for automatic speech recognition based on deep neural net- works.
Optimising The Input Window Alignment in CD-DNN Based Phoneme Recognition for Low Latency Processing
We present a systematic analysis on the performance of a phonetic recogniser when the window of input features is not symmetric with respect to the current frame.
The WaveSurfer Automatic Speech Recognition Plugin
This paper presents a plugin that adds automatic speech recognition (ASR) functionality to the WaveSurfer sound manipulation and visualisation program.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Free Acoustic and Language Models for Large Vocabulary Continuous Speech Recognition in Swedish
This paper presents results for large vocabulary continuous speech recognition (LVCSR) in Swedish.
