Linear predictive coding (LPC) is a well-known approach used to represent speech signals, where speech is modeled as a time-varying system excited by a signal [14, 20]. The LPC coefficients represent the system and, the excitation signals are a train of impulses for voiced signals, and white noise for unvoiced signals. Therefore, speech can be synthesized when its representative system and excitation signal (also termed as the residual) are known. In iJDSP, the LPC function performs linear predictive coding for a given input signal and provides as output the LPC coefficients and the residual. It provides visualizations of the pole-zero plots (Fig 6(e)) and frequency response of the LPC coefficients (Fig 6(b)), and the residual. Using his function, students can build systems to re-synthesize a speech signal. In addition, they can also observe the effects of quantizing the LPC coefficients (Fig. 6(d)) and the residual in the signal-to-noise-Ratio (SNR) of the synthesized signal (Fig. 6(c)).