Mixture Density Networks, Human Articulatory Data and Acoustic-to-articulatory Inversion of Continuous Speech
نویسنده
چکیده
Researchers have been investigating methods for retrieving the articulation underlying an acoustic speech signal for more than three decades. A successful method would find many applications, for example: low bit-rate speech coding, helping individuals with speech and hearing disorders by providing visual feedback during speech training, and the possibility of improved automatic speech recognition.
منابع مشابه
Acoustic-to-articulatory Inversion of Speech: a Review
In this article, we review a specific speech processing research area called acoustic-to-articulatory inversion of speech, or simply speech inversion, which has attracted many researchers and scientists during the last 35 years. The underlying problem refers to the mapping from the acoustic space, which is well-defined since it consists of acoustic signals, to the articulatory space. The latter...
متن کاملHybrid convolutional neural networks for articulatory and acoustic information based speech recognition
Studies have shown that articulatory information helps model speech variability and, consequently, improves speech recognition performance. But learning speaker-invariant articulatory models is challenging, as speaker-specific signatures in both the articulatory and acoustic space increase complexity of speech-to-articulatory mapping, which is already an ill-posed problem due to its inherent no...
متن کاملStatistical mapping between articulatory movements and acoustic spectrum using a Gaussian mixture model
In this paper, we describe a statistical approach to both an articulatory-to-acoustic mapping and an acoustic-to-articulatory inversion mapping without using phonetic information. The joint probability density of an articulatory parameter and an acoustic parameter is modeled using a Gaussian mixture model (GMM) based on a parallel acoustic-articulatory speech database. We apply the GMM-based ma...
متن کاملReconstruction of mistracked articulatory trajectories
Kinematic articulatory data are important for researches of speech production, articulatory speech synthesis, robust speech recognition, and speech inversion. Electromagnetic Articulograph (EMA) is a widely used instrument for collecting kinematic articulatory data. However, in EMA experiment, one or more coils attached to articulators are possible to be mistracked due to various reasons. To ma...
متن کاملA New Bidirectional Neural Network Model for the Acoustic- Articulatory Inversion Mapping For Speech Recognition
In this paper, a new bidirectional neural network for better acoustic-articulatory inversion mapping is proposed. The model is motivated by the parallel structure of human brain, processing information by having forward-inverse connections. In other words, there would be a feedback from articulatory system to the acoustic signals emitted from that organ. Inspired by this mechanism, a new bidire...
متن کامل