For the SwDA corpus, the state-of-the-art baseline result was 71% for more than a decade using a standard Hidden Markov Model (HMM) with language features such as words and n-grams<cite> (Stolcke et al., 2000)</cite> . The inter-annotator agreement accuracy for the same corpus is 84%, and in this particular case, we are still far from achieving human accuracy. However, words like 'yeah' appear in many classes such as backchannel, yes-answer, agree/accept etc.