Sengupta, DeepashreeSnigdha, Farhana, SHu, JiangSapatnekar, Sachin S2017-04-112017-04-112017-04-11https://hdl.handle.net/11299/185544The results of using accurate and approximate finite impulse response (FIR) filters on noisy song clips are summarized here. The names of the clips are listed along with its description. For each song (e.g., Country), there are four versions: a. Country_1NOISY - Noisy version of the song downloaded from the GTZAN Genre Collection (marsyas.info/downloads/datasets.html - use of audio clips permitted by collection creator and falls under fair use). b. Country_2EXACTfilter - Filtered version using exact hardware of the FIR filter c. Country_3APPROXifilterBudget100K - Filtered version using approximate hardware of the FIR filter with error variance 100,000. d. Country_4APPROXifilterBudget200K - Filtered version using approximate hardware of the FIR filter with error variance 200,000. e. Country_5APPROXifilterBudget400K - Filtered version using approximate hardware of the FIR filter with error variance 400,000. The original songs were processed with low pass filter and 6 seconds of each data was selected for our analysis from each of the eight genres specified. Colored noise (high frequency) was added to the 6 seconds data to generate the noisy signal. This signal was then passed through four different versions of an order-33 FIR filter to obtained the filtered versions. Each version of the filter corresponds to the exact, and approximate configurations with three different error variance budgets, and designed using the Selection of Approximate Bits for the Design of Error Tolerant Circuits (SABER) algorithm. While the filtered signal still has some noise, it is within acceptable auditory range of human ears as compared to the noisy signal. Our paper shows how using the approximate version of the FIR filter can lead to power savings compared to the exact version, with minimal compromise on the user experience in terms of the quality of the output.We developed an algorithm, Selection of Approximate Bits for the Design of Error Tolerant Circuits (SABER), to generate an approximate circuit with the aim of maximizing the number of approximate bits in a circuit (which translates to power/area minimization) so that it uses minimal resources under a specified error budget. Our work demonstrates results on fixed-point integer arithmetic operations. The key ingredient of any methodology based on approximate design is an accurate quantification of the error injected into a computation by the approximation scheme. We use the variance of this error as the error metric to be constrained within a user-specified budget. We use an analytical expression of this error variance as a function of the total approximation in a circuit.CC0 1.0 Universal Public Domain Dedicationhttp://creativecommons.org/publicdomain/zero/1.0/Audiohttps://doi.org/10.13020/D6BP4X