> Several sections appear in red, this means they are "0 dB" which indicates a maximum audio level. This is why the recording is distorted I think it's because

> Several sections appear in red, this means they are "0 dB" which indicates a maximum audio level. This is why the recording is distorted I think it's because the signal is normalized, there's no aliasing in the clip which would be the telltale sign of digital clipping. > There is to my knowledge no general algorithm to remove noise from an audio sample. There's quite a lot of research into denoising and blind source separation, simple filtering is kind of a start but as you can tell from the demos doesn't necessarily make it better. Search those terms in the IEEE transactions on DSP/Audio and jAES. > I also applied a high pass filter passing all signals above 260 Hz then a low pass filter passing all signals below 2850 Hz. This reduces the audio signal outside the range of normal human voice, which is probably just noise anyways. This is true in this clip but this description is kind of bad. The human voice absolutely has energy about 2.6k (in fact that's right around where our ears are most sensitive) but this clip does not. Old commercial audio systems had very bad bandwidth due to the limitations of the wiring/transmission, so microphones that typically plugged into them often had what we'd call "bad" frequency responses with higher bass rolloffs (to avoid distortion mangling the voice), lower treble rolloffs (because the materials were cheaper and they didn't care about frequencies that couldn't be transmitted). Basically, if you know what's going to play back the voice is going to be distorted and have limited bandwidth you intentionally highpass filter out the fundamental and accentuate the middle range of the voice which is critical for intelligibility. Paradoxically distortion can help with intelligibility in low doses. This kind of stuff is why restoration is hard, because if you're trying to recover what it sounded like in the room you need to consider the recording system as much as the characteristics of the recorded noise. And it's impossible to know, so some guesswork is needed.