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feature: Add 2.5 ms and 5 ms LC3 plus frame durations

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fix: Check TNS bitstream data

fix: LTPF Activation with 2.5 ms frame sizes
This commit is contained in:
anonymix007
2023-12-13 10:56:20 -08:00
committed by Antoine Soulier
parent a75f187e00
commit 149cb6537e
43 changed files with 3095 additions and 1628 deletions
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131
test/ltpf.py
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@@ -31,7 +31,7 @@ class Resampler_12k8:
self.w = 240 // self.p
self.n = ((T.DT_MS[dt] * 128) / 10).astype(int)
self.d = [ 44, 24 ][dt]
self.d = [ 24, 44 ][dt == T.DT_7M5]
self.x = np.zeros(self.w + T.NS[dt][sr])
self.u = np.zeros(self.n + 2)
@@ -59,7 +59,7 @@ class Resampler_12k8:
x = self.x
u = self.u
### 3.3.9.3 Resampling
### Resampling
h = np.zeros(240 + p)
h[-119:] = T.LTPF_H12K8[:119]
@@ -74,7 +74,7 @@ class Resampler_12k8:
if self.sr == T.SRATE_8K:
u = 0.5 * u
### 3.3.9.4 High-pass filtering
### High-pass filtering
b = [ 0.9827947082978771, -1.9655894165957540, 0.9827947082978771 ]
a = [ 1 , -1.9652933726226904, 0.9658854605688177 ]
@@ -110,7 +110,7 @@ class Resampler_6k4:
if len(self.y) > n:
self.y[-n:] = self.y[:n]
### 3.3.9.5 Downsampling to 6.4 KHz
### Downsampling to 6.4 KHz
h = [ 0.1236796411180537, 0.2353512128364889, 0.2819382920909148,
0.2353512128364889, 0.1236796411180537 ]
@@ -140,11 +140,11 @@ class LtpfAnalysis(Ltpf):
super().__init__(dt, sr)
self.resampler_12k8 = Resampler_12k8(
dt, sr, history = 232)
self.resampler_12k8 = Resampler_12k8(dt, sr,
history = 232 + (32 if dt == T.DT_2M5 else 0))
self.resampler_6k4 = Resampler_6k4(
self.resampler_12k8.n, history = 114)
self.resampler_6k4 = Resampler_6k4(self.resampler_12k8.n,
history = 114 + (16 if dt == T.DT_2M5 else 0))
self.active = False
self.tc = 0
@@ -160,30 +160,32 @@ class LtpfAnalysis(Ltpf):
return 1 + 10 * int(self.pitch_present)
def correlate(self, x, n, k0, k1):
def correlate(self, x, i0, n, k0, k1):
return [ np.dot(x[:n], np.take(x, np.arange(n) - k)) \
for k in range(k0, 1+k1) ]
return np.array([ np.dot(
np.take(x, np.arange(i0, n)),
np.take(x, np.arange(i0, n) - k)) for k in range(k0, 1+k1) ])
def norm_corr(self, x, n, k):
def norm_corr(self, x, i0, n, k):
u = x[:n]
v = np.take(x, np.arange(n) - k)
u = np.take(x, np.arange(i0, n))
v = np.take(x, np.arange(i0, n) - k)
uv = np.dot(u, v)
return uv / np.sqrt(np.dot(u, u) * np.dot(v, v)) if uv > 0 else 0
def run(self, x):
### 3.3.9.3-4 Resampling
### Resampling
x_12k8 = self.resampler_12k8.resample(x)
### 3.3.9.5-6 Pitch detection algorithm
### Pitch detection algorithm
x = self.resampler_6k4.resample(x_12k8)
n = self.resampler_6k4.n
x = self.resampler_6k4.resample(x_12k8)
i0 = [-16, 0][self.dt > T.DT_2M5]
n = self.resampler_6k4.n
r = self.correlate(x, n, 17, 114)
r = self.correlate(x, i0, n, 17, 114)
rw = r * (1 - 0.5 * np.arange(len(r)) / (len(r) - 1))
tc = self.tc
@@ -191,23 +193,24 @@ class LtpfAnalysis(Ltpf):
k1 = min(len(r)-1, tc+4)
t = [ 17 + np.argmax(rw), 17 + k0 + np.argmax(r[k0:1+k1]) ]
nc = [ self.norm_corr(x, n, t[i]) for i in range(2) ]
nc = [ self.norm_corr(x, i0, n, t[i]) for i in range(2) ]
ti = int(nc[1] > 0.85 * nc[0])
self.tc = t[ti] - 17
self.pitch_present = bool(nc[ti] > 0.6)
### 3.3.9.7 Pitch-lag parameter
### Pitch-lag parameter
if self.pitch_present:
tc = self.tc + 17
x = x_12k8
n = self.resampler_12k8.n
x = x_12k8
i0 = [-32, 0][self.dt > T.DT_2M5]
n = self.resampler_12k8.n
k0 = max( 32, 2*tc-4)
k1 = min(228, 2*tc+4)
r = self.correlate(x, n, k0-4, k1+4)
r = self.correlate(x, i0, n, k0-4, k1+4)
e = k0 + np.argmax(r[4:-4])
h = np.zeros(42)
@@ -232,17 +235,21 @@ class LtpfAnalysis(Ltpf):
e = f = 0
self.pitch_index = 0
### 3.3.9.8 Activation bit
### Activation bit
h = np.zeros(24)
h[-7:] = T.LTPF_HI[:7]
h[ :8] = T.LTPF_HI[7:]
x = x_12k8
i0 = [-32, 0][self.dt > T.DT_2M5]
n = self.resampler_12k8.n
k = np.arange(-2, 3)
u = [ np.dot( np.take(x, i-k), np.take(h, 4*k) ) \
for i in range(n) ]
for i in range(i0, n) ]
v = [ np.dot( np.take(x, i-k), np.take(h, 4*k-f) ) \
for i in range(-e, n-e) ]
for i in range(i0-e, n-e) ]
nc = max(0, np.dot(u, v)) / np.sqrt(np.dot(u, u) * np.dot(v, v)) \
if self.pitch_present else 0
@@ -327,7 +334,7 @@ class LtpfSynthesis(Ltpf):
sr = self.sr
dt = self.dt
### 3.4.9.4 Filter parameters
### Filter parameters
pitch_index = self.pitch_index
@@ -346,7 +353,12 @@ class LtpfSynthesis(Ltpf):
self.p_e[0] = int(p * 4 + 0.5) // 4
self.p_f[0] = int(p * 4 + 0.5) - 4*self.p_e[0]
nbits = round(nbytes*80 / T.DT_MS[dt])
nbits = round(nbytes*8 * 10 / T.DT_MS[dt])
if dt == T.DT_2M5:
nbits = int(nbits * (1 - 0.4))
elif dt == T.DT_5M:
nbits = nbits - 160
g_idx = max(nbits // 80, 3+sr) - (3+sr)
g = [ 0.4, 0.35, 0.3, 0.25 ][g_idx] if g_idx < 4 else 0
@@ -355,7 +367,7 @@ class LtpfSynthesis(Ltpf):
self.c_n[0] = 0.85 * g * LtpfSynthesis.C_N[sr][g_idx]
self.c_d[0] = g * LtpfSynthesis.C_D[sr][self.p_f[0]]
### 3.4.9.2 Transition handling
### Transition handling
n0 = (T.SRATE_KHZ[sr] * 1000) // 400
ns = T.NS[dt][sr]
@@ -402,8 +414,7 @@ class LtpfSynthesis(Ltpf):
np.dot(c_d[0], np.take(y , k - d[0] - np.arange(l_d)))
y[k] = yc[k] - (k/n0) * u
### 3.4.9.3 Remainder of the frame
### Remainder of the frame
for k in range(n0, ns):
@@ -466,28 +477,30 @@ def check_resampler(rng, dt, sr):
def check_resampler_appendix_c(dt):
i0 = dt - T.DT_7M5
sr = T.SRATE_16K
ok = True
nt = (5 * T.SRATE_KHZ[sr]) // 4
n = [ 96, 128 ][dt]
k = [ 44, 24 ][dt] + n
n = [ 96, 128 ][i0]
k = [ 44, 24 ][i0] + n
state = initial_hp50_state()
x = np.append(np.zeros(nt), C.X_PCM[dt][0])
x = np.append(np.zeros(nt), C.X_PCM[i0][0])
y = np.zeros(384)
y = lc3.ltpf_resample(dt, sr, state, x, y)
u = y[-k:len(C.X_TILDE_12K8D[dt][0])-k]
u = y[-k:len(C.X_TILDE_12K8D[i0][0])-k]
ok = ok and np.amax(np.abs(u - C.X_TILDE_12K8D[dt][0]/2)) < 2
ok = ok and np.amax(np.abs(u - C.X_TILDE_12K8D[i0][0]/2)) < 2
x = np.append(x[-nt:], C.X_PCM[dt][1])
x = np.append(x[-nt:], C.X_PCM[i0][1])
y[:-n] = y[n:]
y = lc3.ltpf_resample(dt, sr, state, x, y)
u = y[-k:len(C.X_TILDE_12K8D[dt][1])-k]
u = y[-k:len(C.X_TILDE_12K8D[i0][1])-k]
ok = ok and np.amax(np.abs(u - C.X_TILDE_12K8D[dt][1]/2)) < 2
ok = ok and np.amax(np.abs(u - C.X_TILDE_12K8D[i0][1]/2)) < 2
return ok
@@ -503,7 +516,7 @@ def check_analysis(rng, dt, sr):
ltpf = LtpfAnalysis(dt, sr)
t = np.arange(100 * ns) / (T.SRATE_KHZ[sr] * 1000)
s = signal.chirp(t, f0=10, f1=3e3, t1=t[-1], method='logarithmic')
s = signal.chirp(t, f0=10, f1=2500, t1=t[-1], method='logarithmic')
for i in range(20):
@@ -516,7 +529,7 @@ def check_analysis(rng, dt, sr):
(pitch_present_c, data_c) = lc3.ltpf_analyse(dt, sr, state_c, x_c)
ok = ok and (not pitch_present or state_c['tc'] == ltpf.tc)
ok = ok and np.amax(np.abs(state_c['nc'][0] - ltpf.nc[0])) < 1e-2
ok = ok and np.amax(np.abs(state_c['nc'][0] - ltpf.nc[0])) < 1e-1
ok = ok and pitch_present_c == pitch_present
ok = ok and data_c['active'] == data['active']
ok = ok and data_c['pitch_index'] == data['pitch_index']
@@ -537,6 +550,7 @@ def check_synthesis(rng, dt, sr):
x_c = np.zeros(nd+ns)
for i in range(50):
pitch_present = bool(rng.integers(0, 10) >= 1)
if not pitch_present:
synthesis.disable()
@@ -563,37 +577,40 @@ def check_synthesis(rng, dt, sr):
def check_analysis_appendix_c(dt):
i0 = dt - T.DT_7M5
sr = T.SRATE_16K
nt = (5 * T.SRATE_KHZ[sr]) // 4
ok = True
nt = (5 * T.SRATE_KHZ[sr]) // 4
state = initial_state()
x = np.append(np.zeros(nt), C.X_PCM[dt][0])
x = np.append(np.zeros(nt), C.X_PCM[i0][0])
(pitch_present, data) = lc3.ltpf_analyse(dt, sr, state, x)
ok = ok and C.T_CURR[dt][0] - state['tc'] == 17
ok = ok and np.amax(np.abs(state['nc'][0] - C.NC_LTPF[dt][0])) < 1e-5
ok = ok and pitch_present == C.PITCH_PRESENT[dt][0]
ok = ok and data['pitch_index'] == C.PITCH_INDEX[dt][0]
ok = ok and data['active'] == C.LTPF_ACTIVE[dt][0]
ok = ok and C.T_CURR[i0][0] - state['tc'] == 17
ok = ok and np.amax(np.abs(state['nc'][0] - C.NC_LTPF[i0][0])) < 1e-5
ok = ok and pitch_present == C.PITCH_PRESENT[i0][0]
ok = ok and data['pitch_index'] == C.PITCH_INDEX[i0][0]
ok = ok and data['active'] == C.LTPF_ACTIVE[i0][0]
x = np.append(x[-nt:], C.X_PCM[dt][1])
x = np.append(x[-nt:], C.X_PCM[i0][1])
(pitch_present, data) = lc3.ltpf_analyse(dt, sr, state, x)
ok = ok and C.T_CURR[dt][1] - state['tc'] == 17
ok = ok and np.amax(np.abs(state['nc'][0] - C.NC_LTPF[dt][1])) < 1e-5
ok = ok and pitch_present == C.PITCH_PRESENT[dt][1]
ok = ok and data['pitch_index'] == C.PITCH_INDEX[dt][1]
ok = ok and data['active'] == C.LTPF_ACTIVE[dt][1]
ok = ok and C.T_CURR[i0][1] - state['tc'] == 17
ok = ok and np.amax(np.abs(state['nc'][0] - C.NC_LTPF[i0][1])) < 1e-5
ok = ok and pitch_present == C.PITCH_PRESENT[i0][1]
ok = ok and data['pitch_index'] == C.PITCH_INDEX[i0][1]
ok = ok and data['active'] == C.LTPF_ACTIVE[i0][1]
return ok
def check_synthesis_appendix_c(dt):
sr = T.SRATE_16K
ok = True
ok = True
if dt != T.DT_10M:
return ok
@@ -650,7 +667,7 @@ def check():
ok = ok and check_analysis(rng, dt, sr)
ok = ok and check_synthesis(rng, dt, sr)
for dt in range(T.NUM_DT):
for dt in range(T.DT_7M5, T.NUM_DT):
ok = ok and check_resampler_appendix_c(dt)
ok = ok and check_analysis_appendix_c(dt)
ok = ok and check_synthesis_appendix_c(dt)