diff options
Diffstat (limited to 'thirdparty/opus/silk/NLSF2A.c')
| -rw-r--r-- | thirdparty/opus/silk/NLSF2A.c | 59 |
1 files changed, 48 insertions, 11 deletions
diff --git a/thirdparty/opus/silk/NLSF2A.c b/thirdparty/opus/silk/NLSF2A.c index d5b7730638..b1c559ea68 100644 --- a/thirdparty/opus/silk/NLSF2A.c +++ b/thirdparty/opus/silk/NLSF2A.c @@ -66,8 +66,7 @@ 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) */ - int arch /* I Run-time architecture */ + const opus_int d /* I filter order (should be even) */ ) { /* This ordering was found to maximize quality. It improves numerical accuracy of @@ -84,14 +83,15 @@ 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 ); - celt_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 ); @@ -126,15 +126,52 @@ void silk_NLSF2A( a32_QA1[ d-k-1 ] = Qtmp - Ptmp; /* QA+1 */ } - /* Convert int32 coefficients to Q12 int16 coefs */ - silk_LPC_fit( a_Q12, a32_QA1, 12, QA + 1, d ); + /* 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; + } + } - 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 ) ); + if( i == 10 ) { + /* Reached the last iteration, clip the coefficients */ for( k = 0; k < d; k++ ) { - a_Q12[ k ] = (opus_int16)silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ); /* QA+1 -> Q12 */ + 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; } } } |