Index: third_party/opus/src/silk/NLSF2A.c |
diff --git a/third_party/opus/src/silk/NLSF2A.c b/third_party/opus/src/silk/NLSF2A.c |
index b1c559ea68213e06d39de79c977e86f573bd51c8..116b465b1db8c678177adedbc6d25ff9ed387510 100644 |
--- a/third_party/opus/src/silk/NLSF2A.c |
+++ b/third_party/opus/src/silk/NLSF2A.c |
@@ -66,7 +66,8 @@ static OPUS_INLINE void silk_NLSF2A_find_poly( |
void silk_NLSF2A( |
opus_int16 *a_Q12, /* O monic whitening filter coefficients in Q12, [ d ] */ |
const opus_int16 *NLSF, /* I normalized line spectral frequencies in Q15, [ d ] */ |
- const opus_int d /* I filter order (should be even) */ |
+ const opus_int d, /* I filter order (should be even) */ |
+ int arch /* I Run-time architecture */ |
) |
{ |
/* This ordering was found to maximize quality. It improves numerical accuracy of |
@@ -83,15 +84,14 @@ void silk_NLSF2A( |
opus_int32 P[ SILK_MAX_ORDER_LPC / 2 + 1 ], Q[ SILK_MAX_ORDER_LPC / 2 + 1 ]; |
opus_int32 Ptmp, Qtmp, f_int, f_frac, cos_val, delta; |
opus_int32 a32_QA1[ SILK_MAX_ORDER_LPC ]; |
- opus_int32 maxabs, absval, idx=0, sc_Q16; |
silk_assert( LSF_COS_TAB_SZ_FIX == 128 ); |
- silk_assert( d==10||d==16 ); |
+ silk_assert( d==10 || d==16 ); |
/* convert LSFs to 2*cos(LSF), using piecewise linear curve from table */ |
ordering = d == 16 ? ordering16 : ordering10; |
for( k = 0; k < d; k++ ) { |
- silk_assert(NLSF[k] >= 0 ); |
+ silk_assert( NLSF[k] >= 0 ); |
/* f_int on a scale 0-127 (rounded down) */ |
f_int = silk_RSHIFT( NLSF[k], 15 - 7 ); |
@@ -126,52 +126,15 @@ void silk_NLSF2A( |
a32_QA1[ d-k-1 ] = Qtmp - Ptmp; /* QA+1 */ |
} |
- /* Limit the maximum absolute value of the prediction coefficients, so that they'll fit in int16 */ |
- for( i = 0; i < 10; i++ ) { |
- /* Find maximum absolute value and its index */ |
- maxabs = 0; |
- for( k = 0; k < d; k++ ) { |
- absval = silk_abs( a32_QA1[k] ); |
- if( absval > maxabs ) { |
- maxabs = absval; |
- idx = k; |
- } |
- } |
- maxabs = silk_RSHIFT_ROUND( maxabs, QA + 1 - 12 ); /* QA+1 -> Q12 */ |
- |
- if( maxabs > silk_int16_MAX ) { |
- /* Reduce magnitude of prediction coefficients */ |
- maxabs = silk_min( maxabs, 163838 ); /* ( silk_int32_MAX >> 14 ) + silk_int16_MAX = 163838 */ |
- sc_Q16 = SILK_FIX_CONST( 0.999, 16 ) - silk_DIV32( silk_LSHIFT( maxabs - silk_int16_MAX, 14 ), |
- silk_RSHIFT32( silk_MUL( maxabs, idx + 1), 2 ) ); |
- silk_bwexpander_32( a32_QA1, d, sc_Q16 ); |
- } else { |
- break; |
- } |
- } |
+ /* Convert int32 coefficients to Q12 int16 coefs */ |
+ silk_LPC_fit( a_Q12, a32_QA1, 12, QA + 1, d ); |
- if( i == 10 ) { |
- /* Reached the last iteration, clip the coefficients */ |
+ for( i = 0; silk_LPC_inverse_pred_gain( a_Q12, d, arch ) == 0 && i < MAX_LPC_STABILIZE_ITERATIONS; i++ ) { |
+ /* Prediction coefficients are (too close to) unstable; apply bandwidth expansion */ |
+ /* on the unscaled coefficients, convert to Q12 and measure again */ |
+ silk_bwexpander_32( a32_QA1, d, 65536 - silk_LSHIFT( 2, i ) ); |
for( k = 0; k < d; k++ ) { |
- a_Q12[ k ] = (opus_int16)silk_SAT16( silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ) ); /* QA+1 -> Q12 */ |
- a32_QA1[ k ] = silk_LSHIFT( (opus_int32)a_Q12[ k ], QA + 1 - 12 ); |
- } |
- } else { |
- for( k = 0; k < d; k++ ) { |
- a_Q12[ k ] = (opus_int16)silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ); /* QA+1 -> Q12 */ |
- } |
- } |
- |
- for( i = 0; i < MAX_LPC_STABILIZE_ITERATIONS; i++ ) { |
- if( silk_LPC_inverse_pred_gain( a_Q12, d ) < SILK_FIX_CONST( 1.0 / MAX_PREDICTION_POWER_GAIN, 30 ) ) { |
- /* Prediction coefficients are (too close to) unstable; apply bandwidth expansion */ |
- /* on the unscaled coefficients, convert to Q12 and measure again */ |
- silk_bwexpander_32( a32_QA1, d, 65536 - silk_LSHIFT( 2, i ) ); |
- for( k = 0; k < d; k++ ) { |
- a_Q12[ k ] = (opus_int16)silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ); /* QA+1 -> Q12 */ |
- } |
- } else { |
- break; |
+ a_Q12[ k ] = (opus_int16)silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ); /* QA+1 -> Q12 */ |
} |
} |
} |