Constrained structure of ancient Chinese poetry facilitates speech content grouping

Ancient Chinese poetry is constituted by structured language that deviates from ordinary language usage [1, 2]; its poetic genres impose unique combinatory constraints on linguistic elements [3]. How does the constrained poetic structure facilitate speech segmentation when common linguistic [4, 5, 6, 7, 8] and statistical cues [5, 9] are unreliable to listeners in poems? We generated artificial Jueju, which arguably has the most constrained structure in ancient Chinese poetry, and presented each poem twice as an isochronous sequence of syllables to native Mandarin speakers while conducting magnetoencephalography (MEG) recording. We found that listeners deployed their prior knowledge of Jueju to build the line structure and to establish the conceptual flow of Jueju. Unprecedentedly, we found a phase precession phenomenon indicating predictive processes of speech segmentation—the neural phase advanced faster after listeners acquired knowledge of incoming speech. The statistical co-occurrence of monosyllabic words in Jueju negatively correlated with speech segmentation, which provides an alternative perspective on how statistical cues facilitate speech segmentation. Our findings suggest that constrained poetic structures serve as a temporal map for listeners to group speech contents and to predict incoming speech signals. Listeners can parse speech streams by using not only grammatical and statistical cues but also their prior knowledge of the form of language

Speech Transmission Index from running speech : a neural network approach

Speech Transmission Index (STI) is an important objective parameter concerning speech intelligibility for sound transmission channels. It is normally measured with specific test signals to ensure high accuracy and good repeatability. Measurement with running speech was previously proposed, but accuracy is compromised and hence applications limited. A new approach that uses artificial neural networks to accurately extract the STI from received running speech is developed in this paper. Neural networks are trained on a large set of transmitted speech examples with prior knowledge of the transmission channels' STIs. The networks perform complicated nonlinear function mappings and spectral feature memorization to enable accurate objective parameter extraction from transmitted speech. Validations via simulations demonstrate the feasibility of this new method on a one-net-one-speech extract basis. In this case, accuracy is comparable with normal measurement methods. This provides an alternative to standard measurement techniques, and it is intended that the neural network method can facilitate occupied room acoustic measurements

Listening to young children talking on the telephone: a reassessment of Vygotsky's notion of 'egocentric speech'.

In this article the author explores aspects of young children's private speech, examining characteristics of their development of discourse knowledge in utterances that are not directed to actual conversants. Two routes are taken, which the author tries to interlink without seeking a hard and fast juncture. The first is a study of what children are doing when they talk into a toy telephone, with reference to a transcript taken from empirical research. Knowledge of the essential structure of telephone discourse is displayed, as are emotional motivations behind the construction of pretence talk. The second is the notion of 'egocentric speech' as coined by Piaget and developed, within his sociocultural perspective to language acquisition, by Vygotsky. The author argues that dominant contemporary presentations of Vygotsky's notion of 'egocentric speech' tend to stress the self-regulatory or planning function at the expense of its role in expression of the imagination. The two discussions come together in the suggestion that the deployment of the imagination in reassembling sociocultural knowledge for the creation of pretence play, sometimes expressed in private speech, can be a significant factor in the exercise of discourse competencies for young children

Color-to-speech sensory substitution device for the visually impaired

A hardware device is presented that converts color to speech for use by the blind and visually impaired. The use of audio tones for transferring knowledge of colors identified to individuals was investigated but was discarded in favor of the use of direct speech. A unique color-clustering algorithm was implemented using a hardware description language (VHDL), which in-turn was used to program an Altera Corporation's programmable logic device (PLD). The PLD maps all possible incoming colors into one of 24 color names, and outputs an address to a speech device, which in-turn plays back one of 24 voice recorded color names. To the author's knowledge, there are only two such color to speech systems available on the market. However, both are designed to operate at a distance of less than an inch from the surface whose color is to be checked. The device presented here uses original front-end optics to increase the range of operation from less than an inch to sixteen feet and greater. Because of the increased range of operation, the device can not only be used for color identification, but also as a navigation aid