Abstract:
The android speech recognizer acquires
speech at run time through a microphone and
processes the sampled speech to recognize the
uttered text. But the output texts do not match
with users’ data because English and Myanmar
texts are different. This system therefore
proposed a method for obtaining more detail
about actual translation errors in the generated
output by using the Word Error Rate (WER)
based on the string matching algorithms. This
paper has investigated string metrics and
compared the performance of edit distance like
Leveshtein Distance (LD), Q-gram, cosine
similarity and dice coefficient by conducting an
experiment on the Myanmar name using android
speech recognizer output. In order to better fit a
variety of android recognition problem over
strings, using the edit distance of LD is
considered to be an appropriate approach. This
paper shows over several experiments that the
distance obtains goods results in comparison
with other normalized edit distance.
