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DSP3

n     For many years, scientists and engineers have studied the speech production process with the goal of building a system that can start with text and produce speech automatically. In a sense, a text-to-speech synthesizer such as depicted in Figure is a digital simulation of the entire upper part of the speech chain diagram.

n     The input to the system is ordinary text such as an email message or an article from a newspaper or magazine. The first block in the text-to-speech synthesis system, labeled linguistic rules, has the job of converting the printed text input into a set of sounds that the machine must synthesize. The conversion from text to sounds involves a set of linguistic rules that must determine the appropriate set of sounds (perhaps including things like emphasis, pauses, rates of speaking, etc.) so that the resulting synthetic speech will express the words and intent of the text message in what passes for a natural voice that can be decoded accurately by human speech perception. This is more difficult than simply looking up the words in a pronouncing dictionary because the linguistic rules must determine how to pronounce acronyms, how to pronounce ambiguous words like read, bass, object, how to pronounce abbreviations like St. (street or Saint), Dr. (Doctor or drive), and how to properly pronounce proper names, specialized terms, etc.

n     Speech Analysis

n     Short Time Energy

serves to differentiate voiced and unvoiced sounds in speech

from silence (background signal)

– Hamming window (raised cosine window):

Short-Time Magnitude

n     • short-time energy is very sensitive to large

n     signal levels due to x2(n) terms

n     – consider a new definition of ‘pseudo-energy’ based

n     on average signal magnitude (rather than energy)

Short-Time Average ZC Rate