speaking stylea read speech may be in formal styleor spontaneous and conversational with casual style the latter is harder to recognize speaker dependencyspeech can be speaker dependentspeaker adaptiveor speaker independent speaker independent is the hardest to build type of noisenoise is another factor to consider while developing an asr signal to noise ratio may be in various rangesdepending on the acoustic environment that observes less versus more background noiseo if the signal to noise ratio is greater than dbit is considered as high range if the signal to noise ratio lies between db to dbit is considered as medium snr if the signal to noise ratio is lesser than dbit is considered as low range for examplethe type of background noise such as stationarynon-human noisebackground speech and crosstalk by other speakers also contributes to the difficulty of the problem microphone characteristicsthe quality of microphone may be goodaverageor below average alsothe distance between mouth and micro-phone can vary these factors also should be considered for recognition systems despite these difficultiesresearchers worked lot on various aspects of speech such as understanding the speech signalthe speakerand identifying the accents you will have to follow the steps given below to build speech recognizervisualizing audio signals reading from file and working on it this is the first step in building speech recognition system as it gives an understanding of how an audio signal is structured some common steps that can be followed to work with audio signals are as followsrecording when you have to read the audio signal from filethen record it using microphoneat first sampling when recording with microphonethe signals are stored in digitized form but to work upon itthe machine needs them in the discrete numeric form hencewe should perform sampling at certain frequency and convert the signal into the discrete numerical form choosing the high frequency for sampling implies that when humans listen to the signalthey feel it as continuous audio signal example the following example shows stepwise approach to analyze an audio signalusing pythonwhich is stored in file the frequency of this audio signal is , hz