Voice-processing technologies--their application in telecommunications.

As the telecommunications industry evolves over the next decade to provide the products and services that people will desire, several key technologies will become commonplace. Two of these, automatic speech recognition and text-to-speech synthesis, will provide users with more freedom on when, where, and how they access information. While these technologies are currently in their infancy, their capabilities are rapidly increasing and their deployment in today's telephone network is expanding. The economic impact of just one application, the automation of operator services, is well over $100 million per year. Yet there still are many technical challenges that must be resolved before these technologies can be deployed ubiquitously in products and services throughout the worldwide telephone network. These challenges include: (i) High level of accuracy. The technology must be perceived by the user as highly accurate, robust, and reliable. (ii) Easy to use. Speech is only one of several possible input/output modalities for conveying information between a human and a machine, much like a computer terminal or Touch-Tone pad on a telephone. It is not the final product. Therefore, speech technologies must be hidden from the user. That is, the burden of using the technology must be on the technology itself. (iii) Quick prototyping and development of new products and services. The technology must support the creation of new products and services based on speech in an efficient and timely fashion. In this paper I present a vision of the voice-processing industry with a focus on the areas with the broadest base of user penetration: speech recognition, text-to-speech synthesis, natural language processing, and speaker recognition technologies. The current and future applications of these technologies in the telecommunications industry will be examined in terms of their strengths, limitations, and the degree to which user needs have been or have yet to be met. Although noteworthy gains have been made in areas with potentially small user bases and in the more mature speech-coding technologies, these subjects are outside the scope of this paper.

Decoding temporally encoded sensory input by cortical oscillations and thalamic phase comparators

The temporally encoded information obtained by vibrissal touch could be decoded “passively,” involving only input-driven elements, or “actively,” utilizing intrinsically driven oscillators. A previous study suggested that the trigeminal somatosensory system of rats does not obey the bottom-up order of activation predicted by passive decoding. Thus, we have tested whether this system obeys the predictions of active decoding. We have studied cortical single units in the somatosensory cortices of anesthetized rats and guinea pigs and found that about a quarter of them exhibit clear spontaneous oscillations, many of them around whisking frequencies (≈10 Hz). The frequencies of these oscillations could be controlled locally by glutamate. These oscillations could be forced to track the frequency of induced rhythmic whisker movements at a stable, frequency-dependent, phase difference. During these stimulations, the response intensities of multiunits at the thalamic recipient layers of the cortex decreased, and their latencies increased, with increasing input frequency. These observations are consistent with thalamocortical loops implementing phase-locked loops, circuits that are most efficient in decoding temporally encoded information like that obtained by active vibrissal touch. According to this model, and consistent with our results, populations of thalamic “relay” neurons function as phase “comparators” that compare cortical timing expectations with the actual input timing and represent the difference by their population output rate.

Ciliary neurotrophic factor protects striatal output neurons in an animal model of Huntington disease.

Huntington disease is a dominantly inherited, untreatable neurological disorder featuring a progressive loss of striatal output neurons that results in dyskinesia, cognitive decline, and, ultimately, death. Neurotrophic factors have recently been shown to be protective in several animal models of neurodegenerative disease, raising the possibility that such substances might also sustain the survival of compromised striatal output neurons. We determined whether intracerebral administration of brain-derived neurotrophic factor, nerve growth factor, neurotrophin-3, or ciliary neurotrophic factor could protect striatal output neurons in a rodent model of Huntington disease. Whereas treatment with brain-derived neurotrophic factor, nerve growth factor, or neurotrophin-3 provided no protection of striatal output neurons from death induced by intrastriatal injection of quinolinic acid, an N-methyl-D-aspartate glutamate receptor agonist, treatment with ciliary neurotrophic factor afforded marked protection against this neurodegenerative insult.