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+samples/listen/spectrograms/speech_2_output_8k_48k_spec.png filter=lfs diff=lfs merge=lfs -text +samples/listen/spectrograms/speech_3_input_16k_spec.png filter=lfs diff=lfs merge=lfs -text +samples/listen/spectrograms/speech_3_input_8k_spec.png filter=lfs diff=lfs merge=lfs -text +samples/listen/spectrograms/speech_3_output_16k_48k_spec.png filter=lfs diff=lfs merge=lfs -text +samples/listen/spectrograms/speech_3_output_8k_48k_spec.png filter=lfs diff=lfs merge=lfs -text diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..e81421007a6cdb03189d775ab1d2af7830a3c35b --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2024 Jun-Hak Yun + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..0e1112b399e8c415f931d1767d046368c867f812 --- /dev/null +++ b/README.md @@ -0,0 +1,145 @@ +--- +library_name: axera +pipeline_tag: audio-to-audio +base_model: kiriyamaX/FLowHigh_indep_adaptive_400k +language: +- en +- zh +tags: +- axera +- ax650 +- npu3 +- flowhigh +- speech-super-resolution +- audio-super-resolution +- bandwidth-extension +- real-time +- python +--- + +# FlowHigh.AXERA + +**8/16 kHz 语音 → 48 kHz 超分 · AX650 NPU3 · Python RTF 0.24（20–60 s 音频）· 2 个 axmodel 共 58 MB · 不做降噪** + +![RTF](https://img.shields.io/badge/RTF-0.24%20Python-brightgreen) ![Size](https://img.shields.io/badge/axmodel-58%20MB-green) [![GitHub](https://img.shields.io/badge/GitHub-ZY--2012%2FFlowHigh.AXERA-black)](https://github.com/ZY-2012/FlowHigh.AXERA) + +- GitHub: https://github.com/ZY-2012/FlowHigh.AXERA +- 上游: https://github.com/jjunak-yun/FLowHigh_code + +## 目录 + +- 快速开始 +- 结果 +- 推理速度 +- 数据来源 +- License + +## 快速开始（AX650 板端） + +从 HuggingFace 下载 `models/`、`assets/`、`python/`、`samples/`，在包根目录运行： + +```bash +bash run_ax650.sh samples/listen/8k/OSR_us_000_0010_input_8k.wav output.wav +``` + +输入支持 8 kHz / 16 kHz，输出固定 48 kHz。默认 1-step flow、`std=1e-4`；不做降噪。 + +## 结果 + +### 8 kHz 输入（Open Speech / Samplelib） + +#### English + +**OSR_us_000_0010** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +**OSR_us_000_0013** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +**OSR_us_000_0057** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +**OSR_us_000_0059** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +#### Chinese + +**OSR_cn_000_0072** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +**OSR_cn_000_0073** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +**OSR_cn_000_0074** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +**OSR_cn_000_0075** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +#### Samplelib（1 分钟，频谱图为前 10 s） + +**samplelib_speech_1m** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| + +### 16 kHz 参照（人声） + +同一批人声降采样到 16 kHz 后输入；8k 行为 8 kHz 输入，16k 行为 16 kHz 输入。 + +**speech_2** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| +| 16k |
|
| + +**speech_3** + +| 版本 | 输入 | FlowHigh 输出 | +|---|---|---| +| 8k |
|
| +| 16k |
|
| + +## 推理速度：RTF + +| 链路 | Python RTF | +|---|---:| +| 8/16 kHz → 48 kHz | **0.24** | + +20–60 s 音频，1-step flow，BigVGAN 1 s 分块、0.2 s overlap。5 s 短音频因分块/启动开销会略高；C++ 运行时尚未提供。 + +## 数据来源 + +- Open Speech Repository（English / Chinese 8k）：http://voiptroubleshooter.com/open_speech/index.html +- Samplelib speech 1m：https://samplelib.com/mp3/sample-speech-1m.mp3 +- 16 kHz 参照：公开人声样例经 48k->16k 降采样。 + +## License + +MIT；FLowHigh 与 BigVGAN 均为 MIT。模型 checkpoint 来自上游/公开镜像，仓库不重复分发训练权重。 diff --git a/assets/time_emb_4.npy b/assets/time_emb_4.npy new file mode 100644 index 0000000000000000000000000000000000000000..089e4af5aa80f5f5af2cfd926c3662bc4655e33d --- /dev/null +++ b/assets/time_emb_4.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:06284a683d5610206adac80e4764a61f1d77d8cd4d172376513ad5c83d965f0f +size 16512 diff --git a/config.json b/config.json new file mode 100644 index 0000000000000000000000000000000000000000..9e26dfeeb6e641a33dae4961196235bdb965b21b --- /dev/null +++ b/config.json @@ -0,0 +1 @@ +{} \ No newline at end of file diff --git a/models/bigvgan.axmodel b/models/bigvgan.axmodel new file mode 100644 index 0000000000000000000000000000000000000000..8ed9462cb345a01175081e2b645e66b0ea033358 --- /dev/null +++ b/models/bigvgan.axmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4fb5f3a130ef732eea8ef9ac9f365e7bab95d34d176f5926f4a3d21db33306b5 +size 20734384 diff --git a/models/flowhigh.axmodel b/models/flowhigh.axmodel new file mode 100644 index 0000000000000000000000000000000000000000..164a0e377a9520aa571318189422936ce307e27e --- /dev/null +++ b/models/flowhigh.axmodel @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5ed959fdc9632a961204eb3ea8872395102505db96d42730a8c0e1fb6189bd12 +size 38297185 diff --git a/python/demo_board.py b/python/demo_board.py new file mode 100644 index 0000000000000000000000000000000000000000..855216f4a1e4411666aba3a7d4b2b6d33c388837 --- /dev/null +++ b/python/demo_board.py @@ -0,0 +1,107 @@ +import argparse +import time +from pathlib import Path + +import numpy as np +import soundfile as sf + +from flowhigh_sdk import audio + + +def decode_mel(voc, mel, chunk, overlap): + hop = chunk - overlap + wav = None + for s in range(0, mel.shape[-1], hop): + m = mel[..., s:s + chunk] + if m.shape[-1] < chunk: + m = np.pad(m, ((0, 0), (0, 0), (0, chunk - m.shape[-1])), mode="edge") + c = voc.run(None, {"mel": np.ascontiguousarray(m)})[0][0, 0] + if wav is None: + wav = c + else: + n = min(overlap * 480, len(wav), len(c)) + if n > 0: + fade = np.linspace(0.0, 1.0, n, dtype=np.float32) + wav[-n:] = wav[-n:] * (1.0 - fade) + c[:n] * fade + wav = np.concatenate([wav, c[n:]]) + return wav.astype(np.float32) + + +def main(): + p = argparse.ArgumentParser() + p.add_argument("--input", required=True) + p.add_argument("--output", required=True) + p.add_argument("--models", default="models") + p.add_argument("--steps", type=int, default=1) + p.add_argument("--std", type=float, default=1e-4) + p.add_argument("--seed", type=int, default=0) + p.add_argument("--chunk", type=int, default=100) + p.add_argument("--overlap", type=int, default=20) + p.add_argument("--flow-overlap", type=int, default=50) + p.add_argument("--time-emb", default="assets/time_emb_4.npy") + args = p.parse_args() + + x, sr = sf.read(args.input, always_2d=False) + if x.ndim > 1: + x = x.mean(axis=1) + x = np.asarray(x, dtype=np.float32) + target = int(round(audio.SR / sr * x.size)) + x = audio.resample(x, sr) + peak = float(np.max(np.abs(x))) + if peak > 0: + x = x / peak + cond_wave = x.astype(np.float32) + mel = audio.log_mel(cond_wave)[0].T[None] + frames = 500 + if mel.shape[-1] < frames: + mel = np.pad(mel, ((0, 0), (0, 0), (0, frames - mel.shape[-1])), mode="edge") + total = mel.shape[-1] + if total > frames: + n_chunks = (total - frames + (frames - args.flow_overlap) - 1) // (frames - args.flow_overlap) + 1 + padded = frames + (n_chunks - 1) * (frames - args.flow_overlap) + if padded > total: + mel = np.pad(mel, ((0, 0), (0, 0), (0, padded - total)), mode="edge") + padded_total = mel.shape[-1] + + import axengine + + flow = axengine.InferenceSession(str(Path(args.models) / "flowhigh.axmodel")) + voc = axengine.InferenceSession(str(Path(args.models) / "bigvgan.axmodel")) + emb = np.load(args.time_emb).astype(np.float32) + rng = np.random.RandomState(args.seed) + hop = frames - args.flow_overlap + starts = list(range(0, max(1, padded_total - frames + 1), hop)) + + t0 = time.time() + flow_ms = [] + out = None + for s in starts: + c = mel[..., s:s + frames] + y = c + args.std * rng.randn(*c.shape).astype(np.float32) + for i in range(args.steps): + t1 = time.time() + v = flow.run(None, { + "x": np.ascontiguousarray(y), + "cond": np.ascontiguousarray(c), + "time_emb": np.ascontiguousarray(emb[i]), + })[0] + flow_ms.append((time.time() - t1) * 1000) + y = y + (1.0 / args.steps) * v + wav = decode_mel(voc, y, args.chunk, args.overlap) + if out is None: + out = wav + else: + n = min(args.flow_overlap * 480, len(out), len(wav)) + if n > 0: + fade = np.linspace(0.0, 1.0, n, dtype=np.float32) + out[-n:] = out[-n:] * (1.0 - fade) + wav[:n] * fade + out = np.concatenate([out, wav[n:]]) + out = out[:int(total * 480)] + out = audio.postprocess(out, cond_wave[:len(out)], len(out))[:target] + sf.write(args.output, out, audio.SR, subtype="PCM_16") + dt = time.time() - t0 + print(f"chunks={len(starts)} flow_ms={flow_ms} total_ms={dt*1000:.1f} rtf={dt/(x.size/audio.SR):.4f}") + + +if __name__ == "__main__": + main() diff --git a/python/flowhigh_sdk/__init__.py b/python/flowhigh_sdk/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/python/flowhigh_sdk/audio.py b/python/flowhigh_sdk/audio.py new file mode 100644 index 0000000000000000000000000000000000000000..b7ff48beeb7afb04997355dd673675df772ecb93 --- /dev/null +++ b/python/flowhigh_sdk/audio.py @@ -0,0 +1,138 @@ +import numpy as np +from math import gcd + +SR = 48000 +N_FFT = 2048 +HOP = 480 +N_MELS = 256 +FMIN = 20.0 +FMAX = 24000.0 +LOG_FLOOR = 1e-5 +MAG_EPS = 1e-9 + +_MEL = None +_WIN = None + + +def _hz_to_mel(f): + f = np.asarray(f, dtype=np.float64) + f_sp, min_log_hz = 200.0 / 3.0, 1000.0 + min_log_mel = min_log_hz / f_sp + logstep = np.log(6.4) / 27.0 + mel = np.empty_like(f) + lin = f < min_log_hz + mel[lin] = f[lin] / f_sp + mel[~lin] = min_log_mel + np.log(f[~lin] / min_log_hz) / logstep + return mel + + +def _mel_to_hz(m): + m = np.asarray(m, dtype=np.float64) + f_sp, min_log_hz = 200.0 / 3.0, 1000.0 + min_log_mel = min_log_hz / f_sp + logstep = np.log(6.4) / 27.0 + hz = np.empty_like(m) + lin = m < min_log_mel + hz[lin] = m[lin] * f_sp + hz[~lin] = min_log_hz * np.exp(logstep * (m[~lin] - min_log_mel)) + return hz + + +def mel_filterbank(): + global _MEL + if _MEL is None: + freqs = np.linspace(0.0, SR / 2.0, N_FFT // 2 + 1) + edges = np.linspace(_hz_to_mel([FMIN])[0], _hz_to_mel([FMAX])[0], N_MELS + 2) + hz = _mel_to_hz(edges) + fb = np.zeros((N_MELS, freqs.shape[0]), dtype=np.float32) + for m in range(N_MELS): + left, center, right = hz[m], hz[m + 1], hz[m + 2] + up = (freqs - left) / (center - left) + down = (right - freqs) / (right - center) + fb[m] = np.maximum(0.0, np.minimum(up, down)) * (2.0 / max(1e-8, right - left)) + _MEL = fb + return _MEL + + +def hann(): + global _WIN + if _WIN is None: + _WIN = np.hanning(N_FFT + 1)[:-1].astype(np.float64) + return _WIN + + +def log_mel(audio): + x = np.asarray(audio, dtype=np.float64).reshape(-1) + pad = (N_FFT - HOP) // 2 + x = np.pad(x, (pad, pad), mode="reflect") + frames = 1 + (x.size - N_FFT) // HOP + idx = np.arange(N_FFT)[None, :] + HOP * np.arange(frames)[:, None] + spec = np.fft.rfft(x[idx] * hann(), n=N_FFT, axis=1).T + mag = np.sqrt(spec.real ** 2 + spec.imag ** 2 + MAG_EPS) + mel = np.log(np.clip(mel_filterbank() @ mag, LOG_FLOOR, None)) + return mel.T[None].astype(np.float32) + + +def stft(x, center=True, pad_mode="constant"): + x = np.asarray(x, dtype=np.float64).reshape(-1) + if center: + p = N_FFT // 2 + x = np.pad(x, (p, p), mode=pad_mode) + frames = 1 + (x.size - N_FFT) // HOP + idx = np.arange(N_FFT)[None, :] + HOP * np.arange(frames)[:, None] + return np.fft.rfft(x[idx] * hann(), n=N_FFT, axis=1).T + + +def istft(spec, length=None, center=True): + spec = np.asarray(spec) + frames = np.fft.irfft(spec.T, n=N_FFT, axis=1) * hann() + out_len = N_FFT + HOP * (frames.shape[0] - 1) + ola = np.zeros(out_len, dtype=np.float64) + wsum = np.zeros(out_len, dtype=np.float64) + w2 = hann() ** 2 + for i in range(frames.shape[0]): + s = i * HOP + ola[s:s + N_FFT] += frames[i] + wsum[s:s + N_FFT] += w2 + ola /= np.where(wsum > 1e-11, wsum, 1.0) + if center: + ola = ola[N_FFT // 2:len(ola) - N_FFT // 2] + if length is not None: + if ola.size > length: + ola = ola[:length] + elif ola.size < length: + ola = np.pad(ola, (0, length - ola.size)) + return ola.astype(np.float32) + + +def cutoff_bin(spec): + energy = np.cumsum(np.abs(spec).sum(axis=-1)) + if energy[-1] <= 0: + return 0 + limit = energy[-1] * 0.99 + below = np.nonzero(energy < limit)[0] + return int(below[-1]) + 1 if below.size else 0 + + +def postprocess(pred, src, length): + ps = stft(pred, center=True, pad_mode="constant") + ss = stft(src, center=True, pad_mode="constant") + n = min(ps.shape[-1], ss.shape[-1]) + ps, ss = ps[:, :n], ss[:, :n] + cr = cutoff_bin(ss) + merged = ps.copy() + merged[:cr] = ss[:cr] + out = istft(merged, length=length, center=True) + peak = np.max(np.abs(out)) + if peak > 0: + out = out / peak * 0.99 + return out.astype(np.float32) + + +def resample(x, sr_in, sr_out=SR): + x = np.asarray(x, dtype=np.float32).reshape(-1) + if sr_in == sr_out: + return x + g = gcd(int(sr_out), int(sr_in)) + from scipy.signal import resample_poly + return resample_poly(x, sr_out // g, sr_in // g).astype(np.float32) diff --git a/python/requirements.txt b/python/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..e669475e752d10794f132a778c789fc714ad0924 --- /dev/null +++ b/python/requirements.txt @@ -0,0 +1,3 @@ +numpy +scipy +soundfile diff --git a/reports/quantization.md b/reports/quantization.md new file mode 100644 index 0000000000000000000000000000000000000000..83a58ec9bf51f760953637f9c2a95ba3d658b427 --- /dev/null +++ b/reports/quantization.md @@ -0,0 +1,67 @@ +# FlowHigh AX650 quantization report + +## Target + +- Board: AX650N, NPU3, axengine 2.12.0s, compiler 8.0. +- Flow: U16 activations / S8 weights, 38 MB. +- BigVGAN: U16 activations / S8 weights, 20 MB. +- Input: 8 kHz / 16 kHz -> 48 kHz. +- No denoising. + +## Graph split + +```text +host: resample_poly -> log-mel [1,256,T] -> 1-step flow -> BigVGAN chunks -> STFT merge +NPU: flow velocity (37 MB) + BigVGAN 1 s chunks (20 MB) +``` + +The flow NPU input is channel-first `[1,256,500]`; the wrapper transposes to `[1,500,256]` internally. This is required: Pulsar2 lowers 3D tensors channel-first, and feeding `[1,500,256]` directly makes attention run on the wrong axis. + +## Numerical checks + +| Check | Result | +|---|---| +| Flow ONNX vs PyTorch velocity | max err 1.5e-4 | +| Flow U16/S8 on board vs ONNX | SNR 32.96 dB, corr 0.99977 | +| Flow latency, 5 s | 21 ms (after warmup) | +| BigVGAN ONNX vs PyTorch | max err 8.2e-6 | +| BigVGAN U16/S8 on board vs ONNX, 1 s | SNR 20.55 dB, corr 0.99560 | +| BigVGAN latency, 1 s | ~93 ms | +| BigVGAN chunk overlap | 0.2 s; boundary jump reduced from 0.44 to 0.005 | + +BigVGAN is the sensitive part; its direct waveform SNR is low, but the final speech quality after spectral merging is close to the FP32 pipeline. + +## Full pipeline quality + +VCTK `p232_013`, 48 kHz reference. Board uses 1-step flow with `std=1e-4`, BigVGAN 1 s / 0.2 s overlap. Baseline and board use different RNG seeds, so the PESQ/LSD comparison is indicative; flow and BigVGAN SNR rows are strict same-input comparisons. + +| Input | Pipeline | PESQ-WB | STOI | Mel LSD | +|---|---|---|---:|---:| +| 8 kHz | PyTorch FP32 | 3.872 | 0.9981 | 2.323 | +| 8 kHz | AX650 U16/S8 | **3.876** | **0.9982** | 2.333 | +| 16 kHz | PyTorch FP32 | 4.570 | 1.0000 | 2.315 | +| 16 kHz | AX650 U16/S8 | **4.573** | **1.0000** | 2.302 | + +## Speed + +5 s input, Python/axengine, one flow step: + +| Stage | Time | +|---|---:| +| Flow | 33 ms | +| BigVGAN (6 x 1 s chunks) | 578 ms | +| Host STFT/mel/postprocess | ~600 ms | +| Total | 0.94–1.22 s | +| RTF | 0.19–0.24 | + +The current runtime is Python-only. Moving STFT/postprocess to C++ and using a native flow/vocoder loop is the next optimization; the NPU portion itself is 0.61 s for 5 s. + +## Long audio + +The flow graph is fixed at 500 mel frames (5 s). Longer audio is processed in 5 s chunks with 0.5 s overlap and waveform crossfade; BigVGAN uses 1 s chunks with 0.2 s overlap. The 60 s Samplelib input was processed end-to-end with no boundary clicks above the normal waveform derivative. + +## Limitations + +- The 5 s flow chunk is a hard graph size; longer context would need a different compiled graph. +- No denoising; FLowHigh is BWE only. +- C++ runtime is not included in this first quantization milestone. diff --git a/run_ax650.sh b/run_ax650.sh new file mode 100644 index 0000000000000000000000000000000000000000..a5cedbd3291534346bedfd92027daa0d085ba9ad --- /dev/null +++ b/run_ax650.sh @@ -0,0 +1,8 @@ +#!/bin/bash +set -e +cd "$(dirname "$0")" +if [ "$#" -ge 2 ] && [ "${1#-}" = "$1" ]; then + IN="$1"; OUT="$2"; shift 2 + exec python3 python/demo_board.py --models models --steps 1 --std 0.0001 --input "$IN" --output "$OUT" "$@" +fi +exec python3 python/demo_board.py --models models --steps 1 --std 0.0001 "$@" diff --git a/samples/listen/16k/speech_2_input_16k.wav b/samples/listen/16k/speech_2_input_16k.wav new file mode 100644 index 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