Nope. I have never worked with speech input before so am unsure about the data pipeline for the model as well.
So as of now

I have a 52-minute long audio which I have annotated into 7 different categories by preparing a .txt file that looks like:
start-time, end-time, class

and

for feature extraction I have this code

import numpy as np
import librosa
sr = 44100
frame_length = 4096 
hop_length = 1024 
stream = librosa.stream('final.wav', block_length=800, frame_length=frame_length, hop_length=hop_length)

mel_specs_log_zcr = []
for y in stream:
    mel = librosa.feature.melspectrogram(y, sr=sr, center=False, n_fft=4096, hop_length = 1024)
    log_mel=librosa.power_to_db(mel)
    zcr = librosa.feature.zero_crossing_rate(y, center=False, frame_length = 4096, hop_length = 1024 )
    zcr = np.tile(zcr, (128, 1))
    mel_spec_log_zcr = np.stack((log_mel, zcr), axis=2)
    mel_specs_log_zcr.append(mel_spec_log_zcr)