Sentence examples for isolated digit from inspiring English sources

This work presents an application driven digital hardware exploration where we implement real-time, isolated digit speech recognition using a Liquid State Machine.

In 1952, Davis et al. [25] built a system for isolated digit classification for a single speaker.

Simulation results of the proposed composite signal subspace classifier in an isolated digit speech recognition problem reveal an improved performance over its predecessor.

The proposed technique is applied for SVM based isolated digit recognition system and is studied using speaker dependent and multispeaker dependent TI46 database of isolated digits.

It describes the formations of a standard handwritten database, including isolated digits, isolated signs, multi-digit numbers, numerical strings, courtesy amounts, and postal codes.

The CENPARMI Arabic database [11] for offline Arabic handwriting recognition comprises isolated digits, letters, numerical strings and words.

We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits.

Through several intensive processing steps, a huge number of isolated digits, numeral strings, touching digits, dates, words, names, alphabetical letters, free texts, arithmetic, and especial symbols from all these forms were extracted and organized as a standard database.

Adapting this approach, we first use a task independent corpus, BREF [13], and two task dependent databases corresponding, respectively, to isolated digits in a clean environment (BDSON corpus [14]) and voice commands in a noisy environment (VODIS corpus [15]).

For the TI46 isolated digits database, the average recognition rate across several SNRs is improved from 60% (using unmodified MFCCs) to 95% (using the proposed techniques) with additive speech-shaped noise.

The Isolated digits database (0 9, o) has 454 samples for each class.