13. A system that performs a sound-recognition operation, comprising: at least one processor and at least one associated memory; and a sound-recognition system that executes on the at least one processor, wherein during operation, the sound-recognition system, recognizes a sequence of sound primitives in an audio stream, wherein a sound primitive is associated with a semantic label comprising one or more words that describe a sound characterized by the sound primitive, wherein while recognizing the sequence of sound primitives, the sound-recognition system, performs a feature-detection operation on a sequence of sound samples from the audio stream to detect a set of sound features, wherein each sound feature comprises a measurable characteristic for a time window of consecutive sound samples, and wherein detecting the sound feature involves generating a coefficient indicating a likelihood that the sound feature is present in the time window, creates a set of feature vectors from coefficients generated by the feature-detection operation, wherein each feature vector comprises a set of coefficients for sound features in the set of sound features, and identifies the sequence of sound primitives from the sequence of feature vectors; feeds the sequence of sound primitives into a finite-state automaton that recognizes events associated with sequences of sound primitives, and feeds the recognized events into an output system that generates an output associated with the recognized events to be displayed to a user.
13. A system that performs a sound-recognition operation, comprising: at least one processor and at least one associated memory; and a sound-recognition system that executes on the at least one processor, wherein during operation, the sound-recognition system, recognizes a sequence of sound primitives in an audio stream, wherein a sound primitive is associated with a semantic label comprising one or more words that describe a sound characterized by the sound primitive, wherein while recognizing the sequence of sound primitives, the sound-recognition system, performs a feature-detection operation on a sequence of sound samples from the audio stream to detect a set of sound features, wherein each sound feature comprises a measurable characteristic for a time window of consecutive sound samples, and wherein detecting the sound feature involves generating a coefficient indicating a likelihood that the sound feature is present in the time window, creates a set of feature vectors from coefficients generated by the feature-detection operation, wherein each feature vector comprises a set of coefficients for sound features in the set of sound features, and identifies the sequence of sound primitives from the sequence of feature vectors; feeds the sequence of sound primitives into a finite-state automaton that recognizes events associated with sequences of sound primitives, and feeds the recognized events into an output system that generates an output associated with the recognized events to be displayed to a user. 14. The system of claim 13 , wherein the finite-state automaton is a non-deterministic finite-state automaton that can exist in multiple states at the same time; and wherein the non-deterministic finite-state automaton maintains a probability value for each of the multiple states that the finite-state automaton can exist in.