AMAL SURENDRAN
LIKHITH N V
ASWIN K
ADITHYA P P

Speech Recognition is the ability of a machine or program to identify

words and phrases in spoken language and convert them to a machine-
readable format.

Recognizing emotions like anger, happiness, sadness, and neutral from
speech using machine learning algorithms has become an active research
topic lately as a result of the demand for more human interactive
applications.
Emotion recognition systems are mostly implemented in German, English,
Spanish, Dutch, Danish, and other European and Asian languages due to
the avail- ability of datasets for these languages.
However, for Malayalam , there is an extremely limited number of
available speech emotion datasets.
The results were discussed, analyzed, and compared between the three
models using different feature extractions.
Experiments showed that SVM obtained the best accuracy result with
77.14 percent, demonstrating improvement in Malayalam speech emotion
recognition for this classification method.