Sound Synthesis – Are we there yet?

TL;DR. Yes

At the beginning of my PhD, I began to read the sound effect synthesis literature, and I quickly discovered that there was little to no standardisation or consistency in evaluation of sound effect synthesis models – particularly in relations to the sounds they produce. Surely one of the most important aspects of a synthetic system, is whether it can artifically produce a convincing replacement for what it is intended to synthesize. We could have the most intractable and relatable sound model in the world, but if it does not sound anything like it is intended to, then will any sound designers or end users ever use it?

There are many different methods for measuring how effective a sound synthesis model is. Jaffe proposed evaluating synthesis techniques for music based on ten criteria. However, only two of the ten criteria actually consider any sounds made by the synthesiser.

This is crazy! How can anyone know what synthesis method can produce a convincingly realistic sound?

So, we performed a formal evaluation study, where a range of different synthesis techniques where compared in a range of different situations. Some synthesis techniques are indistinguishable from a recorded sample, in a fixed medium environment. In short – Yes, we are there yet. There are sound synthesis methods that sound more realistic than high quality recorded samples. But there is clearly so much more work to be done…

For more information read this paper


Sound Effects Taxonomy

At the upcoming International Conference on Digital Audio Effects, Dave Moffat will be presenting recent work on creating a sound effects taxonomy using unsupervised learning. The paper can be found here.

A taxonomy of sound effects is useful for a range of reasons. Sound designers often spend considerable time searching for sound effects. Classically, sound effects are arranged based on some key word tagging, and based on what caused the sound to be created – such as bacon cooking would have the name “BaconCook”, the tags “Bacon Cook, Sizzle, Open Pan, Food” and be placed in the category “cooking”. However, most sound designers know that the sound of frying bacon can sound very similar to the sound of rain (See this TED talk for more info), but rain is in an entirely different folder, in a different section of the SFx Library.

The approach, is to analyse the raw content of the audio files in the sound effects library, and allow a computer to determine which sounds are similar, based on the actual sonic content of the sound sample. As such, the sounds of rain and frying bacon will be placed much closer together, allowing a sound designer to quickly and easily find related sounds that relate to each other.

Here’s a figure from the paper, comparing the generated taxonomy to the original sound effect library classification scheme.