Acquiring a Lexicon from Unsegmented Speech

Acquiring a Lexicon from Unsegmented Speech Carl de Marcken MIT Artificial Intelligence Laboratory 545 Technology Square, NE43-804 Cambridge, MA, 02139, USA cgdemarc@ai.mit.edu Abstract We present work-in-progress on the ma- chine acquisition of a lexicon from sen- tences that are each an unsegmented phone sequence paired with a primitive represen- tation of meaning. A simple exploratory algorithm is described, along with the di- rection of current work and a discussion of the relevance of the problem for child language acquisition and computer speech recognition. 1 Introduction We are interested in how a lexicon of discrete words can be acquired from continuous speech, a prob- lem fundamental both to child language acquisition and to the automated induction of computer speech recognition systems; see (Olivier, 1968; Wolff, 1982; Cartwright and Brent, 1994) for previous computa- tional work in this area. For the time being, we ap- proximate the problem as induction from phone se- quences rather than acoustic pressure, and assume that learning takes place in an environment where simple semantic representations of the speech intent are available to the acquisition mechanism. For example, we approximate the greater problem as that of learning from inputs like Phon. Input: /~raebltslne~ b~W t/ Sem. Input: { BOAT A IN RABBIT THE BE } (The rabbit's in a boat.) where the semantic input is an unordered set of iden- tifiers corresponding to word paradigms. Obviously the artificial pseudo-semantic representations make the problem much easier: we experiment with them as a first step, somewhere between learning language "from a radio" and providing an unambiguous tex- tual transcription, as might be used for training a speech recognition system. Our goal is to create a program that, after train- ing on many such pairs, can segment a new phonetic utterance into a sequence of morpheme identifiers. Such output could be used as input to many gram- mar acquisition programs. 2 A Simple Prototype We have implemented a simple algorithm as an ex- ploratory effort. It maintains a single dictionary, a set of words. Each word consists of a phone sequence and a set of sememes (semantic symbols). Initially, the dictionary is empty. When presented with an utterance, the algorithm goes through the following sequence of actions: • It attempts to cover ("parse") the utterance phones and semantic symbols with a sequence of words from the dictionary, each word offset a certain distance into the phone sequence, with words potentially overlapping. • It then creates new words that account for un- covered portions of the utterance, and adjusts words from the parse to better fit the utterance. • Finally, it reparses the utterance with the old dictionary and the new words, and adds the new words to the dictionary if the resulting parse covers the utterance well. Occasionally, the program removes rarely-used words from the dictionary, and removes words which can themselves be parsed. The general operation of the program should be made clearer by the follow- ing two examples. In the first, the program starts with an empty dictionary, …

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