import re
from contextlib import contextmanager
from functools import lru_cache
from typing import NamedTuple

import numpy as np
from scipy.io import wavfile
from scipy.signal import butter, sosfilt

SR = 44100
VIOLET, INDIGO, BLUE, CYAN, GREEN, YELLOW, ORANGE, RED = 2200, 1850, 1500, 1150, 800, 550, 380, 250

def env(sig, attack=0.1, release=0.3):
    n = len(sig)
    e = np.ones(n)
    a, r = int(n * attack), int(n * release)
    if a > 0:
        e[:a] = np.linspace(0, 1, a)
    if r > 0:
        e[-r:] *= np.linspace(1, 0, r)
    return sig * e

@lru_cache(maxsize=512)
def _sos(btype, wn, order):
    return butter(order, wn, btype=btype, output='sos')

def bandpass(sig, low, high, order=2):
    low, high = max(20, low), min(SR / 2 - 100, high)
    return sosfilt(_sos('band', (low / (SR / 2), high / (SR / 2)), order), sig)

def lowpass(sig, cutoff, order=2):
    return sosfilt(_sos('low', cutoff / (SR / 2), order), sig)

def highpass(sig, cutoff, order=2):
    return sosfilt(_sos('high', cutoff / (SR / 2), order), sig)

def silence(dur):
    return np.zeros(int(SR * dur))

def _noise(n):
    return np.random.uniform(-1, 1, n)

def _tone(freq, n):
    return np.sin(2 * np.pi * freq * np.arange(n) / SR)

_quiet = False

def _warn(msg):
    if not _quiet:
        print(f"[warning] {msg}")

_VOICE = {'pitch': 1.0, 'formant': 1.0}

VOICE_PRESETS = {
    'neu':  (1.00, 1.00),
    'masc': (0.78, 0.90),
    'fem':  (1.28, 1.10),
}

def set_voice(voice=None, pitch=None, formant=None):
    if voice is not None:
        _VOICE['pitch'], _VOICE['formant'] = VOICE_PRESETS[voice] if isinstance(voice, str) else voice
    if pitch is not None:
        _VOICE['pitch'] = pitch
    if formant is not None:
        _VOICE['formant'] = formant

def _fs(freq):
    return freq * _VOICE['formant']

def pulse(freq, coherent=True, dur=0.09):
    freq = _fs(freq)
    noise = _noise(int(SR * dur))
    return env(bandpass(noise, freq * 0.9, freq * 1.1, order=4) if coherent else noise, 0.02, 0.5)

def _stop(freq, coherent=True, dm=1.0):
    base = 0.09
    closure = silence(base * (dm - 1)) if dm > 1.0 else np.zeros(0)
    return np.concatenate([closure, pulse(freq, coherent, base * min(dm, 1.0))])

def turbulence(freq, coherent=True, dur=0.16):
    freq = _fs(freq)
    n = int(SR * dur)
    shaped = lowpass(_noise(n), freq * 1.3)
    sig = shaped * 0.8 + _tone(freq, n) * 0.3 if coherent else shaped
    return env(sig, 0.1, 0.25)

def sibilant(freq, coherent=True, dur=0.14):
    freq = _fs(freq)
    n = int(SR * dur)
    sig = highpass(_noise(n), 1800 + freq * 0.3)
    if coherent:
        sig = sig * 0.7 + bandpass(_noise(n), freq * 1.5, freq * 2.0, order=4) * 0.5
    return env(sig, 0.03, 0.2)

def hum(freq, coherent=True, dur=0.18):
    freq = _fs(freq)
    n = int(SR * dur)
    tone = (_tone(freq, n) * 0.7 + _tone(freq * 2, n) * 0.25 +
            _tone(freq * 0.5, n) * 0.2 + _tone(freq * 1.005, n) * 0.4)
    sig = tone if coherent else lowpass(_noise(n), freq * 1.4) * 0.85 + tone * 0.15
    return env(sig, 0.1, 0.35)

def flutter(freq, coherent=True, dur=0.22, rate=26):
    freq = _fs(freq)
    n = int(SR * dur)
    phase = (np.arange(n) / SR * rate) % 1.0
    gate = np.clip(1 - 10 * np.abs(phase - 0.2), 0, 1)
    carrier = _tone(freq, n) if coherent else lowpass(_noise(n), freq * 1.4)
    return env(carrier * gate, 0.05, 0.15)

def wave(freq, coherent=True, dur=0.15):
    freq = _fs(freq)
    n = int(SR * dur)
    sig = _tone(freq, n) if coherent else lowpass(_noise(n), freq * 1.2) * 0.85 + _tone(freq, n) * 0.15
    return env(sig, 0.35, 0.4)

def splitwave(freq, coherent=True, dur=0.16):
    freq = _fs(freq)
    n = int(SR * dur)
    if coherent:
        sig = 0.5 * _tone(freq * 0.85, n) + 0.5 * _tone(freq * 1.18, n)
    else:
        ch1 = lowpass(_noise(n), freq * 0.85 * 1.3)
        ch2 = lowpass(_noise(n), freq * 1.18 * 1.3)
        sig = 0.5 * ch1 + 0.5 * ch2
    return env(sig, 0.2, 0.35)

def splitturbulence(freq, coherent=True, dur=0.16):
    freq = _fs(freq)
    n = int(SR * dur)
    ch1 = bandpass(_noise(n), freq * 0.45, freq * 0.75, order=6)
    ch2 = bandpass(_noise(n), freq * 1.25, freq * 1.65, order=6)
    shaped = 0.5 * ch1 + 0.5 * ch2
    if coherent:
        shaped = shaped * 0.8 + _tone(freq, n) * 0.3
    return env(shaped, 0.1, 0.25)

def affricate(freq, coherent=True, dm=1.0):
    return np.concatenate([pulse(freq, coherent, 0.05 * dm), turbulence(freq, coherent, 0.1 * dm)])

def aspiration(dur=0.05):
    return turbulence(GREEN, False, dur) * 0.6

def labialization(dur=0.045):
    return wave(VIOLET, dur=dur) * 0.6

def palatalization(dur=0.045):
    return wave(BLUE, dur=dur) * 0.6

def _build_f0_signal(f0, n):
    if f0 is None:
        return None
    if isinstance(f0, (list, tuple)) and len(f0) > 1:
        bounds = np.linspace(0, n, len(f0)).astype(int)
        curve = np.zeros(n)
        for i in range(len(f0) - 1):
            s, e = bounds[i], bounds[i + 1]
            curve[s:e] = np.linspace(f0[i], f0[i + 1], e - s, endpoint=False)
        curve[-1] = f0[-1]
        return np.sin(np.cumsum(2 * np.pi * curve / SR))
    return _tone(f0[0] if isinstance(f0, (list, tuple)) else f0, n)

def _finish_vowel(sig, n, f0):
    f0_sig = _build_f0_signal(f0, n)
    if f0_sig is not None:
        sig = sig * 0.7 + f0_sig * 0.35
    return env(sig, 0.15, 0.3)

def vowel_glide(freq_pairs, total_dur, f0=None):
    n = int(SR * total_dur)
    if n <= 0:
        return np.zeros(0)
    if len(freq_pairs) == 1:
        f1, f2 = freq_pairs[0]
        return _finish_vowel(0.5 * _tone(f1, n) + 0.5 * _tone(f2, n), n, f0)
    bounds = np.linspace(0, n, len(freq_pairs)).astype(int)
    curves = np.zeros((2, n))
    for i in range(len(freq_pairs) - 1):
        s, e = bounds[i], bounds[i + 1]
        for k in (0, 1):
            curves[k, s:e] = np.linspace(freq_pairs[i][k], freq_pairs[i + 1][k], e - s, endpoint=False)
    curves[:, -1] = freq_pairs[-1]
    phases = np.cumsum(2 * np.pi * curves / SR, axis=1)
    return _finish_vowel(0.5 * np.sin(phases[0]) + 0.5 * np.sin(phases[1]), n, f0)

def _overlap_add(parts, overlap_sec=0.02):
    if not parts:
        return np.zeros(0)
    k0 = int(SR * overlap_sec)
    out = parts[0]
    for p in parts[1:]:
        k = min(k0, len(out), len(p))
        if k > 0:
            out = np.concatenate([out[:-k], out[-k:] + p[:k], p[k:]])
        else:
            out = np.concatenate([out, p])
    return out

TONES = {'`': 260, "'": 220, '-': 185, ',': 150, '.': 115}

_SHAPES = {
    'stop':    lambda f, c, dm: _stop(f, c, dm),
    'glstop':  lambda f, c, dm: pulse(f, c, 0.09 * dm),
    'fric':    lambda f, c, dm: turbulence(f, c, 0.16 * dm),
    'appr':    lambda f, c, dm: wave(f, c, 0.15 * dm),
    'lat':     lambda f, c, dm: splitwave(f, c, 0.16 * dm),
    'tap':     lambda f, c, dm: pulse(f, c, 0.04 * dm),
    'trill':   lambda f, c, dm: flutter(f, c, 0.22 * dm),
    'nasal':   lambda f, c, dm: hum(f, c, 0.18 * dm),
    'affr':    lambda f, c, dm: affricate(f, c, dm),
    'sib':     lambda f, c, dm: sibilant(f, c, 0.14 * dm),
    'latfric': lambda f, c, dm: splitturbulence(f, c, 0.16 * dm),
}

_COLUMNS = [('stop', False), ('stop', True), ('fric', False), ('fric', True), ('appr', True), ('lat', True),
            ('tap', False), ('tap', True), ('trill', True), ('nasal', True),
            ('affr', False), ('affr', True), ('sib', False), ('sib', True), ('latfric', False), ('latfric', True)]

_PLACES = [
    (VIOLET, 'p b ɸ β w ⱳ ᴘ ⱱ ʙ m'),
    (INDIGO, 't d θ ð ɹ l ɍ ɾ r n ʦ ʣ s z ɬ ɮ'),
    (BLUE,   'c ɟ ç ʝ j ʎ ꞔ ƴ ɏ ɲ ʨ ʥ ɕ ʑ ꜿ ỿ'),
    (CYAN,   'q ɢ χ ʁ ɰ ʟ ꝗ ꞡ ʀ ɴ'),
    (GREEN,  'ʔ 7 h ɦ ʕ ꝇ ƕ ʮ ʢ ƞ'),
    (YELLOW, 'ფ ბ ს ზ ჯ ლ ტ წ რ ნ'),
    (ORANGE, 'փ բ ֆ վ ր լ չ ջ ռ մ'),
    (RED,    'Ⱂ Ⰱ Ⱄ Ⰸ Ⰻ Ⰾ Ⱌ Ⰷ Ⱃ Ⰿ'),
]

def _shape(manner, freq, coherent):
    fn = _SHAPES['glstop' if manner == 'stop' and freq == GREEN else manner]
    return lambda dm=1.0: fn(freq, coherent, dm)

CONSONANTS = {}
SONORANT_VOICELESS = {}
for _freq, _row in _PLACES:
    for _sym, (_manner, _voiced) in zip(_row.split(), _COLUMNS):
        CONSONANTS[_sym] = _shape(_manner, _freq, _voiced)
        if _manner in ('appr', 'lat', 'trill', 'nasal'):
            SONORANT_VOICELESS[_sym] = _shape(_manner, _freq, False)

VOWELS = {
    'i': (280, 2250), 'y': (280, 1900), 'ɯ': (280, 1200), 'u': (280, 650),
    'ɪ': (350, 2000), 'ɵ': (420, 1400), 'ʊ': (380, 850),
    'e': (400, 2100), 'ø': (400, 1700), 'ɤ': (400, 1300), 'o': (400, 700),
    'ə': (500, 1500),
    'ɛ': (570, 1900), 'œ': (570, 1600), 'ʌ': (600, 1100), 'ɔ': (550, 850),
    'æ': (700, 1750), 'ɐ': (700, 1400), 'ɑ': (750, 1050),
    'a': (850, 1600),
}

ASCII = {
    'p': 'p', 'b': 'b', 't': 't', 'd': 'd', 'k': 'c', 'g': 'ɟ', 'q': 'q', 'gq': 'ɢ', '?': 'ʔ', '7': '7', 'uvt': 'ფ', 'uvd': 'ბ', 'xrt': 'փ', 'xrd': 'բ', 'gmt': 'Ⱂ', 'gmd': 'Ⰱ',
    'f': 'ɸ', 'v': 'β', 'th': 'θ', 'dh': 'ð', 'kh': 'ç', 'gh': 'ʝ', 'x': 'χ', 'xg': 'ʁ', 'h': 'h', 'hg': 'ɦ', 'uvs': 'ს', 'uvz': 'ზ', 'xrs': 'ֆ', 'xrz': 'վ', 'gms': 'Ⱄ', 'gmz': 'Ⰸ',
    'w': 'w', 'wl': 'ⱳ', 'rz': 'ɹ', 'l': 'l', 'j': 'j', 'lj': 'ʎ', 'jq': 'ɰ', 'lq': 'ʟ', 'jh': 'ʕ', 'lh': 'ꝇ', 'uvj': 'ჯ', 'uvl': 'ლ', 'xrj': 'ր', 'xrl': 'լ', 'gmj': 'Ⰻ', 'gml': 'Ⰾ',
    'rp': 'ᴘ', 'rb': 'ⱱ', 'rh': 'ɍ', 'r': 'ɾ', 'rk': 'ꞔ', 'rj': 'ƴ', 'rq': 'ꝗ', 'rg': 'ꞡ', 'hr': 'ƕ', 'hgr': 'ʮ', 'uvrh': 'ტ', 'uvr': 'წ', 'xrrh': 'չ', 'xrr': 'ջ', 'gmrh': 'Ⱌ', 'gmr': 'Ⰷ',
    'bb': 'ʙ', 'rr': 'r', 'jj': 'ɏ', 'gg': 'ʀ', 'hh': 'ʢ', 'uvrr': 'რ', 'xrrr': 'ռ', 'gmrr': 'Ⱃ',
    'm': 'm', 'n': 'n', 'nj': 'ɲ', 'ng': 'ɴ', 'nh': 'ƞ', 'uvn': 'ნ', 'xrn': 'մ', 'gmn': 'Ⰿ',
    'ts': 'ʦ', 'dz': 'ʣ', 'tsh': 'ʨ', 'dzh': 'ʥ',
    's': 's', 'z': 'z', 'sh': 'ɕ', 'zh': 'ʑ',
    'ls': 'ɬ', 'lz': 'ɮ', 'lsh': 'ꜿ', 'lzh': 'ỿ',

    'i': 'i', 'y': 'y', 'eu': 'ɯ', 'u': 'u',
    'ie': 'ɪ', 'yo': 'ɵ', 'uo': 'ʊ',
    'e': 'e', 'oe': 'ø', 'eo': 'ɤ', 'o': 'o',
    'ea': 'ə',
    'ee': 'ɛ', 'oee': 'œ', 'eoo': 'ʌ', 'oo': 'ɔ',
    'ae': 'æ', 'eaa': 'ɐ', 'aa': 'ɑ', 'a': 'a',
}

SECONDARY = {'>h': aspiration, '>w': labialization, '>j': palatalization}

PLACE_TRANSITION = {
    VIOLET: ('locus', 700),
    INDIGO: ('locus', 1800),
    BLUE:   ('locus', 2400),
    CYAN:   ('perturb', (120, -350)),
}
TRANSITION_PLACE = {
    'p': VIOLET, 'b': VIOLET, 't': INDIGO, 'd': INDIGO,
    'c': BLUE, 'ɟ': BLUE,
    'q': CYAN, 'ɢ': CYAN, 'χ': CYAN, 'ʁ': CYAN,
}

def _place_vowel_transition(place_color, vowel_freqs, dur=0.055):
    entry = PLACE_TRANSITION.get(place_color)
    if entry is None or entry[1] is None:
        return None
    kind, param = entry
    f1, f2 = vowel_freqs
    if kind == 'perturb':
        n = int(SR * 0.07)
        d1, d2 = _fs(param[0]), _fs(param[1])
        f1_curve = np.linspace(f1 + d1, f1, n)
        f2_curve = np.linspace(max(200, f2 + d2), f2, n)
    else:
        n = int(SR * dur)
        if n <= 0:
            return None
        f1_curve = np.full(n, f1)
        f2_curve = np.linspace(_fs(param), f2, n)
    sig = 0.5 * np.sin(np.cumsum(2 * np.pi * f1_curve / SR)) + 0.5 * np.sin(np.cumsum(2 * np.pi * f2_curve / SR))
    return env(sig, 0.08, 0.08) * 1.6

LONG_STEP = 1.8
BRIEF_STEP = 1.8

class Phone(NamedTuple):
    core: str
    secondary: list
    tone: object
    dur: float
    devoiced: bool

def _strip_marks(phon):
    core, secondary = phon, []
    while core[-2:] in SECONDARY:
        secondary.insert(0, core[-2:])
        core = core[:-2]
    devoiced = core.endswith('*')
    if devoiced:
        core = core[:-1]
    stripped = core.rstrip(''.join(TONES))
    tones = tuple(TONES[c] for c in core[len(stripped):])
    core = stripped
    tone_f0 = tones[0] if len(tones) == 1 else (tones or None)
    stripped = core.rstrip(':')
    if len(stripped) != len(core):
        dur_mult, core = LONG_STEP ** (len(core) - len(stripped)), stripped
    else:
        stripped = core.rstrip('+')
        dur_mult = BRIEF_STEP ** -(len(core) - len(stripped))
        core = stripped
    return core, secondary, tone_f0, dur_mult, devoiced

def _parse(phones, translate=None):
    parsed = []
    for p in phones:
        core, secondary, tone, dur, devoiced = _strip_marks(p)
        if translate:
            core = translate.get(core, core)
        parsed.append(Phone(core, secondary, tone, dur, devoiced))
    return parsed

def _group_phones(parsed):
    groups, i = [], 0
    while i < len(parsed):
        if parsed[i].core in VOWELS:
            j = i + 1
            while j < len(parsed) and parsed[j].core in VOWELS:
                j += 1
            groups.append(('v', list(range(i, j))))
            i = j
        else:
            groups.append(('c', i))
            i += 1
    return groups

def _consonant_audio(ph, text, unknown_dur):
    if ph.core not in CONSONANTS:
        _warn(f"unknown phoneme '{text}', inserting silence")
        return silence(unknown_dur)
    if ph.tone is not None:
        _warn(f"tone mark ignored on consonant '{text}'")
    if ph.devoiced and ph.core in SONORANT_VOICELESS:
        audio = SONORANT_VOICELESS[ph.core](ph.dur)
    else:
        if ph.devoiced:
            _warn(f"no voiceless form for consonant '{text}', ignoring '*'")
        audio = CONSONANTS[ph.core](ph.dur)
    if ph.secondary:
        audio = np.concatenate([audio] + [SECONDARY[m]() for m in ph.secondary])
    return audio

def _formants(parsed, run):
    return [(_fs(VOWELS[parsed[i].core][0]), _fs(VOWELS[parsed[i].core][1])) for i in run]

def _onset(parsed, groups, gi, first_pair):
    if gi > 0 and groups[gi - 1][0] == 'c':
        place = TRANSITION_PLACE.get(parsed[groups[gi - 1][1]].core)
        if place is not None:
            return _place_vowel_transition(place, first_pair)
    return None

def _tone_contour(tones):
    if all(t is None for t in tones):
        return None
    filled, last = [], None
    for t in tones:
        if t is None:
            filled.append(185 if last is None else last)
        else:
            filled.extend(t if isinstance(t, tuple) else (t,))
            last = t[-1] if isinstance(t, tuple) else t
    filled = [_VOICE['pitch'] * f for f in filled]
    return filled if len(filled) > 1 else filled[0]

def _render_phones(phones, seg_gap=0.02, vowel_gap=0.004, translate=None):
    parsed = _parse(phones, translate)
    groups = _group_phones(parsed)
    chunks, is_vowel = [], []
    for gi, (kind, ref) in enumerate(groups):
        if kind == 'c':
            chunks.append(_consonant_audio(parsed[ref], phones[ref], 0.01))
        else:
            pairs = _formants(parsed, ref)
            audio = vowel_glide(pairs, sum(0.22 * parsed[i].dur for i in ref),
                                f0=_tone_contour([parsed[i].tone for i in ref]))
            trans = _onset(parsed, groups, gi, pairs[0])
            if trans is not None:
                audio = _overlap_add([trans, audio], 0.015)
            chunks.append(audio)
        is_vowel.append(kind == 'v')
    out = []
    for gi, chunk in enumerate(chunks):
        out.append(chunk)
        if gi < len(chunks) - 1:
            out.append(silence(vowel_gap if is_vowel[gi + 1] else seg_gap))
    return out

NOTE_SEMITONE = {'C': -9, 'C#': -8, 'Db': -8, 'D': -7, 'D#': -6, 'Eb': -6,
                 'E': -5, 'F': -4, 'F#': -3, 'Gb': -3, 'G': -2, 'G#': -1,
                 'Ab': -1, 'A': 0, 'A#': 1, 'Bb': 1, 'B': 2}

def note_to_hz(note):
    if isinstance(note, (int, float)):
        return float(note)
    m = re.match(r'([A-Ga-g][#b]?)(-?\d+)', note)
    if not m:
        raise ValueError(f"unrecognized note name: {note!r}")
    n = NOTE_SEMITONE[m.group(1).capitalize()] + (int(m.group(2)) - 4) * 12
    return 440.0 * 2 ** (n / 12)

def sleep(beats):
    return (None, None, beats)

def render_note_syllable(phoneme_str, note, dur_sec, min_vowel_dur=0.05, xfade=0.02, translate=ASCII):
    hz = note_to_hz(note)
    phones = phoneme_str.split()
    parsed = _parse(phones, translate)
    groups = _group_phones(parsed)
    cons = {ref: _consonant_audio(parsed[ref], phones[ref], 0.03) for kind, ref in groups if kind == 'c'}
    slots = sum(len(ref) for kind, ref in groups if kind == 'v')
    per_vowel = 0.0
    if slots:
        free = dur_sec - sum(len(a) for a in cons.values()) / SR
        per_vowel = max(min_vowel_dur * slots, free) / slots
    chunks = []
    for gi, (kind, ref) in enumerate(groups):
        if kind == 'c':
            chunks.append(cons[ref])
        else:
            pairs = _formants(parsed, ref)
            trans = _onset(parsed, groups, gi, pairs[0])
            if trans is not None:
                chunks.append(trans)
            chunks.append(vowel_glide(pairs, per_vowel * len(ref), f0=hz))
    return _overlap_add(chunks, xfade)

@lru_cache(maxsize=256)
def _note_audio(phoneme_str, note, n, pitch, formant):
    audio = render_note_syllable(phoneme_str, note, n / SR)
    audio.flags.writeable = False
    return audio

def _fit_length(audio, n):
    if len(audio) < n:
        return np.concatenate([audio, np.zeros(n - len(audio))])
    if len(audio) > n:
        out = audio[:n].copy()
        k = min(int(0.01 * SR), n)
        out[-k:] *= np.linspace(1, 0, k)
        return out
    return audio

STRESS_BOOST = 1.35

def _words(seq, translate, seg_gap, word_gap):
    words = seq.split('|')
    out = []
    for wi, group in enumerate(words):
        phones = group.split()
        stressed = bool(phones) and phones[-1] == '!'
        if stressed:
            phones.pop()
        parts = _render_phones(phones, seg_gap, translate=translate)
        audio = np.concatenate(parts) if parts else silence(0)
        out.append(audio * STRESS_BOOST if stressed else audio)
        if wi < len(words) - 1:
            out.append(silence(word_gap))
    return out

def _notes(seq, bpm, note_gap):
    out = []
    for phoneme_str, note, beats in seq:
        slot = max(1, int(round(beats * 60.0 / bpm * SR)))
        if phoneme_str is None:
            out.append(np.zeros(slot))
            continue
        stressed = phoneme_str.endswith('!')
        ps = phoneme_str[:-1] if stressed else phoneme_str
        gap = min(int(note_gap * SR), slot // 2)
        audio = _note_audio(ps, note, slot - gap, _VOICE['pitch'], _VOICE['formant'])
        if stressed:
            audio = audio * STRESS_BOOST
        out += [_fit_length(audio, slot - gap), np.zeros(gap)]
    return out

@contextmanager
def _settings(voice, quiet):
    global _quiet
    prev_voice, prev_quiet = dict(_VOICE), _quiet
    try:
        if voice is not None:
            set_voice(voice)
        _quiet = quiet
        yield
    finally:
        _VOICE.update(prev_voice)
        _quiet = prev_quiet

def synthesize(seq, filename='output.wav', mode='ipa', seg_gap=0.02, word_gap=0.15,
               bpm=100, note_gap=0.01, voice=None, quiet=False):
    if mode not in ('ipa', 'ascii', 'vocaloid'):
        raise ValueError("mode must be 'ipa', 'ascii', or 'vocaloid'")
    with _settings(voice, quiet):
        if mode == 'vocaloid':
            segments = _notes(seq, bpm, note_gap)
        else:
            segments = _words(seq, ASCII if mode == 'ascii' else None, seg_gap, word_gap)
    audio = np.concatenate(segments) if segments else np.zeros(1)
    peak = np.max(np.abs(audio))
    if peak > 0:
        audio = audio / peak * 0.85
    wavfile.write(filename, SR, (audio * 32767).astype(np.int16))
    if not quiet:
        print(f"wrote {filename}")
    return len(audio) / SR

if __name__ == '__main__':
    synthesize("o uo | n o uo", "demo.wav", mode='ascii')