A Chatbot's Take on Hi-Fi Issues

There has been much discussion lately about ChatGPT, the machine-learning– based chatbot from OpenAI. Some experts say it will soon make human writers obsolete. Will that include human hi-fi reviewers?

I decided to engage ChatGPT in an exploratory conversation; think of it as a sort of job interview. What follows has been intensively edited; many words have been removed, but none have been altered. I'm including my own comments in italics.

ChatGPT: Hi-fi,or high fidelity, refers to audio equipment and systems that are designed to reproduce sound as accurately and faithfully as possible. This typically involves using high-quality components and minimizing distortion, noise, and other artifacts.

Jim Austin: Some people prefer "analog" sources—vinyl records and reel-to-reel tape—while others prefer digital technologies, including high-resolution digital files. What is your take?

ChatGPT: [Analog] formats can produce a warm and natural sound, and many audiophiles and music enthusiasts prefer the tactile experience of handling and playing physical media. However, analog formats can also be prone to noise, such as pops, clicks, and hiss, and they can degrade over time. Digital audio formats, on the other hand, use digital signals to encode and decode audio information. Digital audio offers several advantages over analog formats, including the ability to store large amounts of music in a compact space, the ability to easily copy and transfer audio files, and the ability to more easily manipulate the audio signal. Digital audio is generally considered to be more resistant to degradation over time than analog formats.

ChatGPT is making some solid points but leaving out crucial technical information, such as digital's superior S/N ratio and dynamic range capability.

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Jim Austin: One key controversy in hi-fi is about how audio performance should be judged, between those who value measurements most and those who think that to judge music reproduction you must listen.

ChatGPT: Proponents of [the objectivist] approach argue that objective measurements can provide a reliable and unbiased way to evaluate audio performance and that they can help identify the best products and techniques for achieving high-quality sound. [The subjectivist] approach relies on the listener's subjective judgment of factors like the clarity, balance, timbre, and overall musicality of the sound. Proponents of this approach argue that subjective listening is essential to understanding the musical experience and that objective measurements do not always accurately reflect the perceived quality of the sound.

I asked what parts of a hi-fi system are most important. ChatGPT refused to commit, but gave surprising prominence to cables:

ChatGPT: There is scientific evidence that suggests that cables can have a measurable impact on the quality of the audio signal. For example, cables can introduce resistance, capacitance, and inductance into the signal path, which can affect the frequency response and phase relationships of the signal. Cables can also pick up electromagnetic interference (EMI) and radio frequency interference (RFI) from other electronic devices, which can introduce noise and distortion into the signal. These effects can be quantified using objective measurements, and they suggest that cables can have a measurable impact on the sound.

On the other hand, some people argue that the differences introduced by cables are too small to be audible and that the perceived differences in sound quality are due to psychological factors or to differences in the other components of the hi-fi system. Some studies have attempted to quantify the audible differences between different types of cables using double-blind listening tests, but the results of these studies have been mixed and are often disputed.

A reasonable take. I then chose a hi-fi topic at random—MQA—to see how far ChatGPT would follow me into hi-fi's weeds.

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ChatGPT: MQA technology uses a combination of techniques to capture and reproduce high-resolution audio, including advanced audio compression algorithms, digital filtering, and time-stretching. MQA files are typically encoded at a higher bit depth and sample rate than standard audio files, which allows them to capture a greater range of audio information and produce a more detailed and accurate reproduction of the original sound.

ChatGPT, here, is confused about several points, but the term "time-stretching" is especially curious. I asked for more information.

ChatGPT: In MQA technology, time-stretching is used to adjust the length of an audio signal in order to match the original recording. This is done by analyzing the audio data and identifying the musical structure of the signal, such as the tempo and the rhythms of the individual instruments. The audio data is then processed to stretch or compress the signal as needed to match the original recording.

I commented: "MQA does talk about time-smearing, but I've never heard 'time-stretching' in the context of MQA." This led to the first of several apologies.

ChatGPT: I apologize for the error. You are correct that MQA technology uses a process called "time-smearing" rather than "time-stretching." Time-smearing is a technique that is used in MQA technology to reduce the amount of data required to represent an audio signal, while still preserving the full range of audio information from the original recording.

ChatGPT now seems to be confusing time-smearing with Audio Origami. I pointed out the error. First another apology, then:

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ChatGPT: You are correct that time-smearing in the context of MQA technology refers to the effect of digital-to-analog and analog-to-digital conversions on transients in the music. To address this issue, MQA technology uses a technique called "time-smearing" to compensate for the effects of time-smearing on transients in the music.

Wait, MQA uses time-smearing to compensate for time-smearing?

ChatGPT: Yes, that's correct! MQA technology uses a technique called "time-smearing" to compensate for the effects of time-smearing on transients in the music.

I came away impressed by ChatGPT's compositional abilities—its ability to summarize and present information coherently—but I was surprised (even stunned) by its strange errors and how it persisted in defending those errors almost as if trying to save face—not unlike certain audio reviewers. Still, it will be a while before Stereophile employs chatbots to write its reviews.

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