In pursuit of visemes
نویسندگان
چکیده
We describe preliminary work towards an objective method for identifying visemes. Active appearance model (AAM) features are used to parameterise a speaker’s lips and jaw during speech. The temporal behaviour of AAM features between automatically identified salient points is used to represent visual speech gestures, and visemes are created by clustering these gestures using dynamic time warping (DTW) as a costfunction. This method produces a significantly more structured model of visual speech than if a typical phoneme-to-viseme mapping is assumed.
منابع مشابه
Comparison of Different Types of Visemes using a Constraint-based Coarticulation Model
A common approach to producing visual speech is to interpolate the parameters describing a sequence of mouth shapes, known as visemes, where visemes are the visual counterpart of phonemes. A single viseme typically represents a group of phonemes that are visually similar. Often these visemes are based on the static poses used in producing a phoneme. In this paper we investigate alternative repr...
متن کاملPrototyping and Transforming Visemes for Animated Speech
Animated talking faces can be generated from a set of predefined face and mouth shapes (visemes) by either concatenation or morphing. Each facial image corresponds to one or more phonemes, which are generated in synchrony with the visual changes. Existing implementations require a full set of facial visemes to be captured or created by an artist before the images can be animated. In this work w...
متن کاملHMM-based visual speech synthesis using dynamic visemes
In this paper we incorporate dynamic visemes into hidden Markov model (HMM)-based visual speech synthesis. Dynamic visemes represent intuitive visual gestures identified automatically by clustering purely visual speech parameters. They have the advantage of spanning multiple phones and so they capture the effects of visual coarticulation explicitly within the unit. The previous application of d...
متن کاملA Novel Visual Speech Representation and HMM Classification for Visual Speech Recognition
This paper presents the development of a novel visual speech recognition (VSR) system based on a new representation that extends the standard viseme concept (that is referred in this paper to as Visual Speech Unit (VSU) and Hidden Markov Models (HMM). The visemes have been regarded as the smallest visual speech elements in the visual domain and they have been widely applied to model the visual ...
متن کاملUnderstanding the visual speech signal
For machines to lipread, or understand speech from lip movement, they decode lip-motions (known as visemes) into the spoken sounds. We investigate the visual speech channel to further our understanding of visemes. This has applications beyond machine lipreading; speech therapists, animators, and psychologists can benefit from this work. We explain the influence of speaker individuality, and dem...
متن کامل