A rust implementation of the Arbitrary Rate Discrete Fourier Transform Sample Rate Converter (ARDFTSRC) algorithm.
ardftsrc is a high-quality audio sample-rate converter, and is appropriate for both realtime and offline resampling.
Generally ardftsrc is preferred over other resamplers when quality is paramount. Although it is generic over both f32 and f64, it is highly recommended to use it with f64, even when processing an f32 audio stream.
It is ranked among the top scoring resampling libraries on HydrogenAudio Sample Rate Conversion Comparison, topping out with a balanced score of 99.84%. It is more compute intensive than other resamplers, so consider sinc rubato if you want more efficiency. See PERFORMANCE.md for a detailed speed and quality comparison vs rubato.
Use InterleavedResampler::process_all to resample a complete interleaved audio stream for a single track.
use ardftsrc::{InterleavedResampler, PRESET_HIGH};
fn resample_all(input: &[f32], in_rate: usize, out_rate: usize, channels: usize) -> Vec<f32> {
// When using a preset other than "FAST", f64 processing is preferred.
let input_f64: Vec<f64> = input.iter().map(|v| *v as f64).collect();
let config = PRESET_HIGH
.with_input_rate(in_rate)
.with_output_rate(out_rate)
.with_channels(channels);
let mut resampler = InterleavedResampler::<f64>::new(config).unwrap();
let output = resampler.process_all(&input_f64).unwrap();
// Convert back to the original interleaved f32
output.interleave().into_iter().map(|v| v as f32).collect()
}Use chunk resampling when you can control both read and write buffer sizes. Query input_buffer_size() and output_buffer_size() and size your input and output slices to the sizes required. The chunk API is more efficient than the streaming API and is preferred when you are not doing live resampling.
There are two chunked resamplers depending on the shape of your audio:
InterleavedResampler- for interleaved audioPlanarResampler- for planar audio.
Internally ardftsrc uses planar representation, so PlanarResampler is more efficient, but if you're already working with interleaved audio, prefer InterleavedResampler since it has an optimized de-interleave / re-interleave path. Working with all chunked resamplers is the same:
- Create the resampler with
let resampler = Resampler::new(config) - Query the required input buffer size and output buffer size with
resampler.input_buffer_size()andresampler.output_buffer_size() - Call
process_chunk(...)for each chunk, using the appropriate buffer sizes. - Call
process_chunk_final(...)for the final chunk, it can be undersized. - Finally, call
finalize(...)once per stream to emit delayed tail samples and reset stream state.
use ardftsrc::{InterleavedResampler, PRESET_GOOD};
fn resample_chunked(input: Vec<f32>, in_rate: usize, out_rate: usize, channels: usize) -> Vec<f32> {
// When using a preset other than "FAST", f64 processing is preferred.
let input_f64: Vec<f64> = input.into_iter().map(|v| v as f64).collect();
let config = PRESET_GOOD
.with_input_rate(in_rate)
.with_output_rate(out_rate)
.with_channels(channels);
let mut resampler = InterleavedResampler::<f64>::new(config).unwrap();
// Get the input and output chunk sizes
// You must read and write in these buffer sizes
let input_chunk_size = resampler.input_buffer_size();
let output_chunk_size = resampler.output_buffer_size();
let mut out_buf = vec![0.0_f64; output_chunk_size];
let mut out_f64 = Vec::<f64>::new();
let mut offset = 0;
// Process whole chunks in the size of input_chunk_size
while offset + input_chunk_size <= input_f64.len() {
let chunk = &input_f64[offset..offset + input_chunk_size];
// Process the chunk
let written = resampler.process_chunk(chunk, &mut out_buf).unwrap();
// Process output
out_f64.extend_from_slice(&out_buf[..written]);
offset += input_chunk_size;
}
// The final chunk can be undersized (or even zero sized)
let final_chunk = &input_f64[offset..];
// Process Output
let written = resampler.process_chunk_final(final_chunk, &mut out_buf).unwrap();
out_f64.extend_from_slice(&out_buf[..written]);
// After processing the final chunk, you must call "finalize()" to get tail content.
// finalize() also resets the resampler instance so it can be used again.
let written = resampler.finalize(&mut out_buf).unwrap();
out_f64.extend_from_slice(&out_buf[..written]);
// Convert back into f32
out_f64.into_iter().map(|v| v as f32).collect()
}For adjacent tracks, you can set edge context before processing:
pre(Vec<T>): tail frames from the previous trackpost(Vec<T>): head frames from the next track
post(...) may be called any time while the current stream is still active, but it must be
set before process_chunk_final(...).
This enables live gapless handoff: while track A is streaming, once track B is known you can
call post(...) on A with B's head samples so A's stop-edge uses real next-track context.
ardftsrc-rs provides both rodio integration via RodioResampler (rodio feature) and the ability to build your own custom realtime audio resampling pipeline via RealtimeResampler.
Enable the rodio feature to use RodioResampler to wrap a rodio::Source and resample it in realtime in your rodio pipeline.
When playing from a buffered audio source such as a file or a buffered stream, it is recommended to use config.with_rodio_fast_start(true), which will
avoid initial output delay by pulling samples from the upstream source to prime the resampler. For very-realtime sources such as microphones or similar,
do not enable fast-start.
#[cfg(feature = "rodio")]
{
let stream = rodio::DeviceSinkBuilder::open_default_sink()?;
let mixer = stream.mixer();
let tone = rodio::source::SignalGenerator::new(
NonZero::new(44_100 as u32).unwrap(),
400, // 400 Hz
rodio::source::Function::Sine,
)
.take_duration(Duration::from_secs(3.0));
let config = PRESET_FAST.with_channels(1).with_input_rate(44_100).with_output_rate(48_000);
let resampled_tone = RodioResampler::new(tone, config)?;
mixer.add(resampled_tone);
std::thread::sleep(Duration::from_secs(4));
}More examples can be found:
- Basic rodio example:
examples/rodio_adapter.rs - Span-switching rodio example:
examples/rodio_adapter_with_spans.rs
Use batching when you have multiple full tracks to convert with the same configuration.
InterleavedResampler::batch(...): processes each interleaved input as an independent stream (no context shared between tracks).InterleavedResampler::batch_gapless(...): preserves adjacent-track context for gapless album-style playback.PlanarResamplerexposes the samebatch(...)andbatch_gapless(...)APIs for already-planar inputs.
Enable the rayon feature to parallelize work across tracks.
use ardftsrc::{InterleavedResampler, PRESET_GOOD, PlanarVecs};
fn resample_tracks(
inputs: &[&[f64]],
in_rate: usize,
out_rate: usize,
channels: usize,
) -> Vec<PlanarVecs<f64>> {
let config = PRESET_GOOD
.with_input_rate(in_rate)
.with_output_rate(out_rate)
.with_channels(channels);
let driver = InterleavedResampler::<f64>::new(config).unwrap();
// Independent tracks (podcasts, unrelated files, etc.).
let _independent = driver.batch(inputs).unwrap();
// Gapless sequence (album tracks played back-to-back).
let gapless = driver.batch_gapless(inputs).unwrap();
// Return one of the two results based on your use case.
gapless
}ARDFTSRC is built for quality over speed, and despite supporting both f32 and f64 should almost always be run as f64. To resample f32 audio, it is recommended to convert f32 samples to f64, resample them using InterleavedResampler<f64> or PlanarResampler<f64>, then convert back to f32.
If you want better performance than what this project offers, consider using a sinc resampler such as rubato.
Presets are pre-vetted Config for various quality levels.
let config = ardftsrc::PRESET_GOOD
.with_input_rate(44_100)
.with_output_rate(48_000)
.with_channels(2);| Preset | Quality | Bandwidth | Recommended use | Quality metrics |
|---|---|---|---|---|
PRESET_FAST |
512 |
0.832 |
Fast preset for realtime workloads. | f32, f64 |
PRESET_GOOD † |
1878 |
0.911 |
Balanced preset for realtime quality. | f64 |
PRESET_HIGH |
73622 |
0.987 |
High quality for offline use. | f64 |
PRESET_EXTREME |
524514 |
0.995 |
Maximum quality, intended for offline use. | f64 |
† You should probably use PRESET_GOOD. It's fast, has very high quality metrics, and has lower pre-ringing artefact as compared PRESET_HIGH and PRESET_EXTREME.
If you need to support very large downsampling ratios (e.g. 192kHz → 8kHz), set .with_decimate(true) to speed things up. It enables a conservative pre-decimator (only at ratios of 4:1 or higher) that applies progressive 2:1 decimations before the main resampling stage. It is designed so the FFT stage still performs at least a genuine 2:1 reduction of its own, and respects the configured bandwidth.
let config = ardftsrc::Config::new(192_000, 8_000, 1).with_decimate(true);It's a speed/memory optimization, not a way to reduce buffering or latency — for that, lower quality instead. If you do lower quality for a large ratio, turn decimate on too: it keeps a low-quality conversion sounding good at ratios where it would otherwise struggle.
By default the low-pass transition ends at the lower Nyquist frequency and everything beyond it is suppressed. Setting an alias_floor lets the transition extend past Nyquist, which makes it wider and reduces ringing. Energy in the extended region is folded back (downsampling) or imaged (upsampling), but only down to the floor, and never into the passband set by bandwidth.
// Fold only down to where the filter response is -3 dB.
let config = ardftsrc::Config::new(48_000, 44_100, 2).with_alias_floor_db(-3.0);This is not the same as removing the low-pass filter: the passband is unchanged, and content above the extended stopband is still suppressed. Alias rejection is intentionally reduced. Pre-decimation stages stay strict.
On the command line, use -a / --allow-aliasing (equivalent to --alias-floor-db -3), --alias-floor <fraction>, or --alias-floor-db <dB>.
| Flag | Enables | Default |
|---|---|---|
rodio |
rodio integration via rodio::RodioResampler |
No |
rayon |
Parallelized resampling (batch() and process_all() APIs) |
No |
avx |
FFT AVX SIMD | Yes |
sse |
FFT SSE SIMD | Yes |
neon |
FFT NEON SIMD for ARM / Mac | Yes |
wasm_simd |
FFT WebAssembly SIMD | Yes |
audioadapter |
Experimental audioadapter support |
No |
high_precision |
Double-double, f128, and f256 precision FFT backends for extreme quality |
No |
Runtime feature detection is in place for all SIMD except webassembly.
The workspace includes a small utility cli, ardftsrc-rs, for WAV/FLAC sample-rate conversion.
You can use this as a utility, or use it to benchmark this project.
Processing defaults to f64. Pass --f32 for 32-bit float processing (quality is capped at 8192, so --preset high and --preset extreme are rejected). --f32 decodes, resamples, and encodes in f32 without an f64 round-trip. A compatible Vulkan GPU is used automatically when one is available: f64 needs shaderFloat64 (not available on Apple GPUs), while --f32 can run on any real GPU. Pass --cpu to force CPU even when a GPU is available. --gpu-group-chunks and --gpu-ring-slots tune GPU batching (defaults are both 4). Configurations the GPU backend cannot run (--decimate, --high-precision) stay on CPU. Pass --high-precision double-double|f128|f256 to use a high-precision FFT backend (much slower; for extreme quality).
RUSTFLAGS="-C target-cpu=native" cargo build --release
./target/release/ardftsrc-rs --help
./target/release/ardftsrc-rs --input in.wav --output out.flac --output-rate 48000 --preset high
./target/release/ardftsrc-rs --input in.wav --output out.flac --output-rate 48000 --preset good --f32
./target/release/ardftsrc-rs --input in.wav --output out.flac --output-rate 48000 --preset extreme \
--taper-type beta_cdf --alpha 10 --beta 10 --dd-fft --decimate --phase -0.5Select --taper-type tanh --alpha 3 for an endpoint-normalized hyperbolic
tangent transition. With the bessel feature enabled, --taper-type kbd
selects the descending half of a standard Kaiser–Bessel-derived window, and
--taper-type half_kaiser (also half-kaiser) selects a descending half-Kaiser
shifted and scaled to reach zero at the stopband. Both default to --alpha 6
and use Kaiser beta = pi × alpha, like the existing cumulative bessel taper.
The library variants are TaperType::Tanh(alpha), TaperType::Kbd(alpha), and
TaperType::HalfKaiser(alpha). All require finite, positive alpha.
Detailed quality reports are available for each preset:
You can generate reports using the ardftsrc-report command, a CLI that generates per-preset quality
reports combining two independent measurements:
-
HydrogenAudio scores: runs ardftsrc through the HydrogenAudio SRC, test suite. Requires GNU Octave (with the
signalandimagepackages) onPATH. -
THD+N (total harmonic distortion + noise): Measure frequency, amplitude, sample-rate pair, and preset, fitting each resampled output against a steady-state sine to measure distortion.
cargo run -p ardftsrc-report --release -- all --out-dir reportsContributions are welcome!
At a high level there are two layers:
ArdftsrcCore<T>is the core DSP engine. It owns FFT and runs the core ARDFTSRC algorithm. It is private.PlanarResampler<T>andInterleavedResampler<T>are fixed-size chunk resamplers. They own oneArdftsrcCoreper channel and expose full-buffer, chunked, and batch processing APIs for planar or interleaved audio.AdapterResampler<T>is optional behind theaudioadapterfeature and adapts generic audioadapter inputs and outputs onto the chunk resampling core. Right now there are performance issues with this.RealtimeResampler<T>provides arbitrary-size sample buffering for live resampling.
The golden_hashes test validates resampler determinism against checked-in golden outputs in test_wavs/golden_hashes.<arch>.json. It is intended to catch unintended behavior changes.
Run it with:
cargo test -p ardftsrc --release --features=rayon golden_hashes -- --nocaptureTo regenerate test_wavs/golden_hashes.<arch>.json:
rust-script scripts/generate_golden_hashes.rsUpdates to test_wavs/golden_hashes.<arch>.json are allowed, but only when accompanied by verifiable quality improvements demonstrated with the HydrogenAudio SRC test suite.
AI use is allowed for the following:
- Code exploration and understanding
- Generating tests
- Creating normal code / function blocks as long as the code is then manually and carefully hand-edited by a human
- Add bindings to other languages, python, cpp, c#, ts (wasm) etc.
- Investigate why the optional audioadapter interface appears to be much slower than other paths.
