WO2012144127A1 - ハフマン符号化を実行するための装置および方法 - Google Patents
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- 238000013139 quantization Methods 0.000 claims abstract description 43
- 230000000873 masking effect Effects 0.000 claims description 35
- 230000003595 spectral effect Effects 0.000 claims description 18
- 238000001228 spectrum Methods 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000011084 recovery Methods 0.000 claims description 2
- 238000004364 calculation method Methods 0.000 claims 5
- 238000007689 inspection Methods 0.000 claims 2
- 230000008054 signal transmission Effects 0.000 claims 2
- 230000005236 sound signal Effects 0.000 abstract description 9
- 230000004069 differentiation Effects 0.000 abstract 2
- 238000010586 diagram Methods 0.000 description 8
- 230000001052 transient effect Effects 0.000 description 6
- 238000009795 derivation Methods 0.000 description 5
- 230000007423 decrease Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000010354 integration Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000009365 direct transmission Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
- G10L19/032—Quantisation or dequantisation of spectral components
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/0017—Lossless audio signal coding; Perfect reconstruction of coded audio signal by transmission of coding error
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
- G10L19/0204—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders using subband decomposition
- G10L19/0208—Subband vocoders
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
- G10L19/0212—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders using orthogonal transformation
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
- H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
Definitions
- the present invention relates to an audio / speech encoding apparatus, an audio / speech decoding apparatus, and an audio / speech encoding method and decoding method that use Huffman coding.
- Huffman coding In signal compression, Huffman coding is widely used, and an input signal is coded using a variable length (VL) code table (Huffman table). Huffman coding is more efficient than fixed length (FL) coding for input signals with non-uniform statistical distribution.
- VL variable length
- FL fixed length
- the Huffman table is derived by a specific method based on the estimated appearance probability of each possible value of the input signal. During encoding, each input signal value is mapped to a specific variable length code in the Huffman table.
- signal statistics may differ significantly from one set of audio signals to another set of audio signals. Even within the same set of audio signals.
- the bit consumption due to Huffman coding may be much higher than the bit consumption due to fixed length coding.
- One possible solution is to include both Huffman coding and fixed length coding in the coding and select the coding method that consumes fewer bits. In order to indicate which encoding method has been selected in the encoder, one flag signal is transmitted to the decoder side. This solution is based on the newly standardized ITU-T speech codec G. 719.
- Voice codec G standardized by ITU-T.
- Huffman coding is used in coding the norm factor quantization index.
- the input signal sampled at 48 kHz is processed by the transient state detector (101). Depending on the detection of the transient, a high frequency resolution conversion or a low frequency resolution conversion (102) is applied to the input signal frame. Acquired spectral coefficients are grouped into bands of unequal length. The norm of each band is estimated (103) and the resulting spectral envelope consisting of the norms of all bands is quantized and encoded (104). The coefficients are then normalized by the quantized norm (105). The quantized norm is further adjusted based on the adaptive spectral weighting (106) and used as an input for bit allocation (107). The normalized spectral coefficients are lattice vector quantized and encoded based on the bits assigned to each frequency band (108). The level of unencoded spectral coefficients is estimated, encoded (109) and transmitted to the decoder. Huffman coding is applied to the quantization indices of both the encoded spectral coefficients and the encoded norm.
- the frame flag that is, the transient flag indicating whether the frame is stationary or transient is first decoded.
- the spectral envelope is decoded and the same bit exact norm adjustment and bit allocation algorithm is used at the decoder to recalculate the bit allocation required to decode the quantized index of the normalized transform coefficients.
- the norm factor of the spectral subband is scalar quantized using a uniform logarithmic scalar quantizer using 40 3 dB steps.
- the codebook entry for the logarithmic quantizer is shown in FIG. As can be seen from the code book, the range of norm factors is [2 ⁇ 2.5 , 2 17 ], and the value decreases as the index increases.
- the encoding of the norm factor quantization index is shown in FIG. There are a total of 44 subbands, corresponding to 44 norm factors.
- the norm factor is quantized using the first 32 codebook entries (301), while the other norm factors are the 40 codebook entries shown in FIG. Is scalar quantized (302).
- the norm factor quantization index of the first subband is encoded directly using 5 bits (303), while the indices of the other subbands are encoded by differential encoding.
- the difference index is encoded by two possible methods: fixed length encoding (305) and Huffman encoding (306).
- a Huffman table for the difference index is shown in FIG. This table has a total of 32 entries from 0 to 31, taking into account the possibility of sudden energy changes between adjacent subbands.
- the sound pressure level required to make a sound perceivable when another sound (masking sound) is present is defined as a masking threshold in audio coding.
- the masking threshold depends on the frequency and the sound pressure level of the masking sound. When two sounds have similar frequencies, the masking effect is large and the masking threshold is also large. When the masking sound has a large sound pressure level, it has a strong masking effect on other sounds and the masking threshold is also large.
- one subband when one subband has a very large energy, it has a large masking effect with respect to other subbands, particularly with respect to adjacent subbands. In that case, the masking threshold of the other subbands, particularly the adjacent subbands, is large.
- the listener cannot perceive the deterioration of the sound component in the subband.
- the present invention provides an apparatus and method that utilizes audio signal characteristics to generate a Huffman table and to select a Huffman table from a set of predefined tables during audio signal encoding. Is done.
- the auditory masking property is used to narrow the range of the difference index, so that a Huffman table with fewer code words can be designed and used for encoding. Since the Huffman table has fewer codewords, it is possible to design code codes that are shorter in length (consuming fewer bits). In this way, the overall bit consumption for encoding the difference index can be reduced.
- ITU-T G Diagram showing the framework of 719 Diagram showing codebook for norm factor quantization Diagram showing the process of norm factor quantization and encoding Diagram showing a Huffman table used for norm factor index encoding Diagram showing a framework that employs the present invention Figure showing an example of a predefined Huffman table Figure showing an example of a predefined Huffman table Diagram showing derivation of masking curve Diagram showing how to narrow the range of the difference index Flow chart showing how to change the index Diagram showing how a Huffman table can be designed
- FIG. 5 shows the codec of the present invention, which comprises an encoder and a decoder that apply the inventive idea to Huffman coding.
- subband energy is processed by a psychoacoustic model (501) to derive a masking threshold Mask (n).
- a masking threshold Mask n
- the quantization index of the norm factor of the subband whose quantization error is lower than the masking threshold is changed so that the range of the difference index can be made smaller (502).
- a Huffman table designed for that particular range in a set of predefined Huffman tables is selected (505) for differential index encoding (506).
- the range [12, 18].
- the Huffman table designed for [12, 18] is selected as the Huffman table for encoding.
- This set of pre-defined Huffman tables is designed and configured according to the range of the difference index (details will be explained later).
- a flag signal indicating the selected Huffman table and a coding index are transmitted to the decoder side.
- Huffman table Another way to select a Huffman table is to use all Huffman tables to calculate all bit consumption and then select the Huffman table that consumes the fewest bits.
- FIG. 1 a set of four predefined Huffman tables is shown in FIG.
- Table 6.1 shows the range of the flag signal and the corresponding Huffman table.
- Table 6.2 shows the Huffman codes for all values in the range [13,17].
- Table 6.3 shows the Huffman codes for all values in the range [12,18].
- Table 6.4 shows the Huffman codes for all values in the range [11, 19].
- Table 6.5 shows the Huffman codes for all values in the range [10, 20].
- the corresponding Huffman table is selected for decoding the difference index (508) according to the flag signal (507).
- FIG. 7 shows the derivation of the masking curve of the input signal.
- the energy of the subbands is calculated, and using these energies, a masking curve for the input signal is derived.
- some existing techniques such as a masking curve derivation method in the MPEG AAC codec can be used.
- FIG. 8 shows how the range of the difference index is narrowed.
- a comparison is made between the masking threshold and the subband quantization error energy. For subbands whose quantization error energy is below the masking threshold, the index is changed to a value closer to the adjacent subband, but the corresponding quantization error energy exceeds the masking threshold so that sound quality is not affected. No change is guaranteed. After the change, the index range can be narrowed. This will be described below.
- the index can be changed as follows (subband 2 is used as an example). As shown in FIG. 2, a large index corresponds to a smaller energy, where Index (1) is smaller than Index (2). The change in Index (2) is actually to decrease its value. It can be done as shown in FIG.
- Diff_index (1) Index (1) -Index (0) +15, n ⁇ [1,43]. . . (Formula 5)
- New_Diff_index (1) New_Index (1) -New_Index (0) +15, n ⁇ [1,43]. . . (Expression 6) ⁇ New_index (1) -New_Index (0) ⁇ Index (1) -Index (0) ⁇ New_diff_Index (1) -15 ⁇ Diff_Index (1) -15. . . (Formula 7)
- the subband energy is processed by the psychoacoustic model (1001) to derive a masking threshold Mask (n).
- a masking threshold Mask Mask (n)
- the quantization index of the norm factor of the subband whose quantization error energy is below the masking threshold is changed so that the range of the difference index can be made smaller (1002).
- the difference index of the changed index is calculated (1003).
- the range of the difference index for Huffman coding is identified (1004). For each range value, all input signals having the same range are collected and the probability distribution of each value of the difference index within the range is calculated.
- Huffman table For each range value, one Huffman table is designed according to the probability. In order to design the Huffman table, several conventional Huffman table design methods can be used here.
- a difference index between the original quantization indexes is calculated.
- the original difference index and the new difference index are compared to see if they consume the same bits.
- the changed difference index is restored to the original difference index. If the original difference index and the new difference index do not consume the same number of bits, the codeword in the Huffman table that is closest to the original difference index and consumes the same number of bits is selected as the recovered difference index. .
- the advantage of this embodiment is that the quantization error of the norm factor can be made smaller, but the bit consumption is the same as in the first embodiment.
- a subband energy and a predefined energy ratio threshold change the quantization index of that particular subband. Used to determine whether to do (1201). As the following equation shows, if the energy ratio between the current subband and the adjacent subband is below the threshold, the current subband is not considered as important and changes the quantization index of the current subband can do.
- the quantization index can be changed as shown in the following equation.
- the advantage of this embodiment is that it can avoid very complex and complex psychoacoustic models.
- Diff_index (n) Index (n) -Index (n-1) +15. . . (Equation 10)
- Diff_index (n) means a difference index of subband n
- index (n) means a quantization index of subband n
- index (n-1) means subband. It means n-1 quantization index.
- the change is performed according to the difference index value and threshold value of the preceding subband.
- Diff_index (n) means the difference index of subband n
- Diff_index (n ⁇ 1) means the difference index of subband n ⁇ 1
- Diff_index_new (n) means a new difference index of subband n
- Threshold means a value for checking whether or not the difference index should be changed.
- the norm factor representing energy also has a sudden change from the preceding frequency band, and the quantization index of the norm factor suddenly increases or decreases with a large value. In that case, a very large or very small differential index results.
- one module in order to completely reconstruct the difference index, one module (1403) named “reconstruction of difference index” is implemented.
- the reconstruction is performed according to the difference index value and threshold value of the preceding subband.
- the threshold at the decoder is the same as the threshold used at the encoder.
- Diff_index (n) means a difference index of subband n
- Diff_index (n ⁇ 1) means a difference index of subband n ⁇ 1
- Diff_index_new (n) means a new difference index of subband n
- Threshold means a value for checking whether or not the difference index should be reconstructed.
- the first difference index is not changed at the encoder side, but can be received directly and fully reconstructed, and then the second difference
- the index can be reconstructed according to the value of the first difference index, and then the third difference index, the fourth difference index, and the subsequent indexes can be reconfigured by following the same procedure. It can be completely reconfigured.
- the advantage of this embodiment is that the differential index can still be completely reconstructed on the decoder side while the range of the differential index can be reduced. Therefore, it is possible to improve the bit efficiency while maintaining the bit indexness of the quantization index.
- Each functional block used in the description of the above embodiment can be generally implemented as an LSI constituted by an integrated circuit. These can be individual chips or can be partly or wholly contained on a single chip.
- LSI is adopted, but this may also be referred to as “IC”, “system LSI”, “super LSI”, or “ultra LSI” depending on the different degree of integration.
- the method of circuit integration is not limited to LSI, and implementation using a dedicated circuit or a general-purpose processor is also possible. It is also possible to use an FPGA (Field Programmable Gate Array) or a reconfigurable processor that can reconfigure the connection and setting of circuit cells in the LSI after the LSI is manufactured.
- FPGA Field Programmable Gate Array
- reconfigurable processor that can reconfigure the connection and setting of circuit cells in the LSI after the LSI is manufactured.
- An encoding apparatus, a decoding apparatus, and an encoding method and a decoding method according to the present invention include a wireless communication terminal apparatus, a base station apparatus in a mobile communication system, a telephone conference terminal apparatus, a video conference terminal apparatus, and a voice over Internet protocol (VOIP) terminal device.
- VOIP voice over Internet protocol
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Abstract
Description
図5は、本発明のコーデックを示しており、本発明のコーデックは、本発明の考案をハフマン符号化に適用する、エンコーダおよびデコーダを備える。
ハフマン符号化の差分インデックスの範囲は、以下の式に示されるように識別される(504)。範囲=[Min(Diff_index(n)),Max(Diff_index(n))] ...(式3)
この実施の形態では、ビット節約を維持できるが、差分インデックスを元の値により近い値に回復する方法が導入される。
この実施の形態では、心理音響モデルの使用を回避して、何らかのエネルギー比閾値だけを使用する方法が導入される。
この実施の形態では、差分インデックスの範囲を狭めながらも、差分インデックスを完全に再構成できる方法が導入される。
102 変換
103 ノルム推定
104 ノルム量子化および符号化
105 スペクトル正規化
106 ノルム調整
107 ビット割り当て
108 格子ベクトル量子化および符号化
109 ノイズレベル調整
110 多重化
111 逆多重化
112 格子復号
113 スペクトルフィル生成器
114 包絡線整形
115 逆変換
301 スカラ量子化(32個のステップ)
302 スカラ量子化(40個のステップ)
303 直接的伝送(5ビット)
304 差分
305 固定長符号化
306 ハフマン符号化
501 心理音響モデル
502 インデックスの変更
503 差分
504 範囲の検査
505 ハフマン符号テーブルの選択
506 ハフマン符号化
507 ハフマンテーブルの選択
508 ハフマン復号
509 合算
1001 心理音響モデル
1002 インデックスの変更
1003 差分
1004 範囲の検査
1005 確率
1006 ハフマン符号の導出
1101 心理音響モデル
1102 インデックスの変更
1103 差分
1104 範囲の検査
1105 ハフマン符号テーブルの選択
1106 差分
1107 差分インデックスの回復
1108 ハフマン符号化
1201 インデックスの変更
1202 差分
1203 範囲の検査
1204 ハフマン符号テーブルの選択
1205 ハフマン符号化
1301 差分
1302 差分インデックスの変更
1303 範囲の検査
1304 ハフマン符号テーブルの選択
1305 ハフマン符号化
1401 ハフマン符号テーブルの選択
1402 ハフマン符号化
1403 差分インデックスの再構成
1404 合算
Claims (13)
- 時間領域入力信号を周波数領域信号に変換する変換部と、
入力信号の周波数スペクトルを複数のサブバンドに分割する帯域分割部と、
各サブバンドのエネルギーのレベルを表すノルムファクタを導出するノルムファクタ計算部と、
前記ノルムファクタを量子化する量子化部と、
量子化インデックスを変更するインデックス変更部と、
いくつかの事前定義されたハフマンテーブルの中からハフマンテーブルを選択するハフマンテーブル選択部と、
前記選択されたハフマンテーブルを使用して、前記インデックスを符号化するハフマン符号化部と、
前記選択されたハフマンテーブルを示すフラグ信号を伝送するフラグ信号伝送セッションと
を備えるオーディオ/音声符号化装置。 - 前記インデックス変更部が、
各サブバンドの前記エネルギーを計算するエネルギー計算部と、
各サブバンドのマスキング閾値を導出する心理音響モデル部と、
量子化誤差が前記導出されたマスキング閾値を下回るサブバンドを識別する検査部と、
前記識別されたサブバンドのインデックスを変更するインデックス変更部であって、前記変更が、前記識別されたサブバンドのインデックスをその隣接サブバンドのインデックスにより近づける一方で、新しいインデックスの量子化誤差が、依然として前記導出されたマスキング閾値を下回ることが保証される、インデックス変更部と
を備える、請求項1に記載のオーディオ/音声符号化装置。 - 前記インデックス変更部が、
各サブバンドの前記エネルギーを計算するエネルギー計算部と、
エネルギーが隣接サブバンドのエネルギーの一定のパーセンテージを下回るサブバンドを識別する検査部と、
前記識別されたサブバンドのインデックスを変更するインデックス変更部であって、前記変更が、前記識別されたサブバンドのインデックスをその隣接サブバンドのインデックスにより近づける、インデックス変更部と
を備える、請求項1に記載のオーディオ/音声符号化装置。 - 前記ハフマンテーブル選択が、
前記インデックスの範囲を計算する範囲計算部と、
前記計算された範囲のために事前定義されたハフマンテーブルを選択するハフマンテーブル選択部と
を備える、請求項1に記載のオーディオ/音声符号化装置。 - 前記ハフマンテーブル選択が、
すべての前記事前定義されたハフマンテーブルのビット消費を計算するビット消費計算部と、
消費するビットが最も少ないハフマンテーブルを選択するハフマンテーブル選択部と
を備える、請求項1に記載のオーディオ/音声符号化装置。 - 前記ハフマン符号化部が、
前記変更されたインデックス値を、同数のビットを消費するが、元のインデックスにより近い値に回復するインデックス回復部と、
前記回復されたインデックスを符号化するハフマン符号化部と
を備える、請求項1に記載のオーディオ/音声符号化装置。 - 前記ハフマン符号化部が、
現在のサブバンドと先行サブバンドの間の差分インデックスを計算する差分インデックス計算部と、
前記差分インデックスを符号化するハフマン符号化部と
を備える、請求項1に記載のオーディオ/音声符号化装置。 - 時間領域入力信号を周波数領域信号に変換する変換部と、
入力信号の周波数スペクトルを複数のサブバンドに分割する帯域分割部と、
各サブバンドのエネルギーのレベルを表すノルムファクタを導出するノルムファクタ計算部と、
前記ノルムファクタを量子化する量子化部と、
現在のサブバンドと先行サブバンドの間の差分インデックスを計算する差分インデックス計算部と、
前記差分インデックスの範囲を縮小するために、前記差分インデックスを変更する差分インデックス変更部であって、前記変更が、前記先行サブバンドの差分インデックスが定義された範囲を上回った、または下回った場合に限って、差分インデックスに対して行われる、差分インデックス変更部と、
いくつかの事前定義されたハフマンテーブルの中からハフマンテーブルを選択するハフマンテーブル選択部と、
前記選択されたハフマンテーブルを使用して、前記差分インデックスを符号化するハフマン符号化部と、
前記選択されたハフマンテーブルを示すフラグ信号を伝送するフラグ信号伝送部と
を備えるオーディオ/音声符号化装置。 - 前記差分インデックス変更部が、
前記先行サブバンドの前記差分インデックスと前記定義された範囲に対応する境界との間の差分に従って、オフセット値を計算するオフセット値計算部と、
前記先行サブバンドの前記差分インデックスが前記定義された範囲を下回った場合に、現在の差分インデックスから前記オフセット値を減算し、前記先行サブバンドの前記差分インデックスが前記定義された範囲を上回った場合に、現在の差分インデックスに前記オフセット値を加算する、変更部と
を備える、請求項8に記載のオーディオ/音声符号化装置。 - 選択されたハフマンテーブルを示すフラグ信号を復号するフラグ信号復号セッションと
前記フラグ信号に従って、ハフマンテーブルを選択するハフマンテーブル選択部と、
前記選択されたハフマンテーブルを使用して、インデックスを復号するハフマン復号部と、
ノルムファクタを逆量子化する逆量子化部と、
前記ノルムファクタを用いてスペクトル係数を再構成する係数再構成部と、
周波数領域入力信号を時間領域信号に変換する変換部と
を備えるオーディオ/音声復号装置。 - 前記ハフマン復号部が、
差分インデックスを復号するハフマン復号部と、
前記復号された差分インデックスを使用して、量子化インデックスを計算するインデックス計算部と
を備える、請求項10に記載のオーディオ/音声復号装置。 - 前記ハフマン復号部が、
差分インデックスを復号するハフマン復号部と、
前記差分インデックスの値を再構成する差分インデックス再構成部であって、前記再構成が、先行サブバンドの差分インデックスが定義された範囲を上回った、または下回った場合に限って、差分インデックスに対して行われる、差分インデックス再構成部と、
前記復号された差分インデックスを使用して、量子化インデックスを計算するインデックス計算部と
を備える、請求項10に記載のオーディオ/音声復号装置。 - 前記差分インデックス再構成部が、
前記先行サブバンドの前記差分インデックスと前記定義された範囲に対応する境界との間の差分に従って、オフセット値を計算するオフセット値計算部と、
前記先行サブバンドの前記差分インデックスが前記定義された範囲を下回った場合に、現在の差分インデックスから前記オフセット値を減算し、前記先行サブバンドの前記差分インデックスが前記定義された範囲を上回った場合に、現在の差分インデックスに前記オフセット値を加算する、変更部と
を備える、請求項12に記載のオーディオ/音声復号装置。
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