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手植记:让农产品身价翻倍的竟然是TA

手植记:让农产品身价翻倍的竟然是TA

  让农产品身价翻倍的竟然是TA

  生活是由柴米油盐这些简单到乏味的元素组成的,可是很少有人注意到这些乏味的元素也有个性和态度,在人人都想把自己与别人区别开来,人人又都想在别人那里获得共鸣的社会里,原生食材网店恰恰迎合了社会的需求,层出不穷的个性化标签,就成了用最低成本提升自己生活质量的一种乐趣。

  首先,给农产品赋予一种生活态度。

  在众多诸如:南食召、把文翰、故乡车站、手植记的农产品食材网店中。我们选择最近发展迅猛的手植记为例具体分析。

  1)所有食材,都有故事

  手植记的创意最早来自于某创意公司CEO的一个小私心,他觉得原生食材确实是难得的好物,就想着找来给员工发福利,改善一下员工的生活品质,却意外发现人们对原生食材需求很大,就干脆把他做成一个品牌,没想到竟迅速赢得大众的认可,也积累了不少忠实的顾客。

  他们为所有食材都安装了一个故事,这些故事包含房价,堵车,加班,雾霾和地沟油这些80后生活中的标签元素,每一个故事都让他们“感同身受”,一句“光活着就已经竭尽全力”,就引起了普通社会人最深刻的共鸣。

  2)除了食粮,还快递精神。

  从单品的商品命名到商品本身的故事,用商品的营养价值功效来和购买人群挂钩。

  举例来说,手植记为“经常应酬,为了家庭幸福又不能不经常出差或异地奋斗”的年轻人量身定制了两款农产品:“公关经理的复活剂”和“漂泊者的相思豆”。

  这样的产品命名迎合匹配了社会人物画像。从产品的名字看到了身处社会的自己,无论是看还是触摸手植记都有一份感动。

  其次,有很多附加服务。

  还是以手植记为例。手植记不光要运营网站,更要打通所有SNS渠道。让消费者不光知道要什么生活,更知道该如何享受这种生活。

  1) 小植食谱:

  手植记的微博会教给你关于农产品的百种做法,让你不会买完了产品就结束了体验,你可以通过微博完成对产品的最终消化,这种另类的关怀,的确让不少消费者感受到了生活中的小甜蜜。

  2)小植话题:

  在这个版块里,关于美食的一切你都能获得。比如最近大火的电影特工学院,在小植话题中居然有关于电影中所有酒的饮酒指南,不但让消费者再次回味了特工大叔的绅士风度,也拓宽了手植记形象的覆盖范围。

  手植记

  我们快乐&精神食粮

  为生活寻找原生态食材

Contents
List of Figures
List of Tables
Contributing Authors
Introduction
Karlheinz Brandenburg and Mark Kahrs
Audio quality determination based on perceptual measurement techniques 1
John G. Beerends
1.1 Introduction 1
1.2 Basic measuring philosophy 2
1.3 Subjective versus objective perceptual testing 6
1.4 Psychoacoustic fundamentals of calculating the internal sound representation
8
1.5 Computation of the internal sound representation 13
1.6 The perceptual audio quality measure (PAQM) 17
1.7 Validation of the PAQM on speech and music codec databases 20
1.8 Cognitive effects in judging audio quality 22
1.9 ITU Standardization 29
1.9.1 ITU-T, speech quality 30
1.9.2 ITU-R, audio quality 35
1. 10 Conclusions 37
2
Perceptual Coding of High Quality Digital Audio 39
Karlheinz Brandenburg
2.1 Introduction 39
vi APPLICATIONS OF DSP TO AUDIO AND ACOUSTICS
2.2 Some Facts about Psychoacoustics
2.2.1 Masking in the Frequency Domain
2.2.2 Masking in the Time Domain
2.2.3 Variability between listeners
2.3 Basic ideas of perceptual coding
2.3.1 Basic block diagram
2.3.2 Additional coding tools
2.3.3 Perceptual Entropy
2.4 Description of coding tools
2.4.1 Filter banks
2.4.2 Perceptual models
2.4.3 Quantization and coding
2.4.4 Joint stereo coding
2.4.5 Prediction
2.4.6 Multi-channel: to matrix or not to matrix
2.5 Applying the basic techniques: real coding systems
2.5.1 Pointers to early systems (no detailed description)
2.5.2 MPEG Audio
2.5.3 MPEG-2 Advanced Audio Coding (MPEG-2 AAC)
2.5.4 MPEG-4 Audio
2.6 Current Research Topics
2.7 Conclusions
Reverberation Algorithms
William G. Gardner
3.1 Introduction
3.1.1 Reverberation as a linear filter
3.1.2 Approaches to reverberation algorithms
3.2 Physical and Perceptual Background
3.2.1 Measurement of reverberation
3.2.2 Early reverberation
3.2.3 Perceptual effects of early echoes
3.2.4 Reverberation time
3.2.5 Modal description of reverberation
3.2.6 Statistical model for reverberation
3.2.7 Subjective and objective measures of late reverberation
3.2.8 Summary of framework
3.3 Modeling Early Reverberation
3.4 Comb and Allpass Reverberators
3.4.1 Schroeder’s reverberator
3.4.2 The parallel comb filter
3.4.3 Modal density and echo density
3.4.4 Producing uncorrelated outputs
3.4.5 Moorer’s reverberator
3.4.6 Allpass reverberators
3.5 Feedback Delay Networks
3.5.1 Jot’s reverberator 119
3.5.2 Unitary feedback loops 121
3.5.3 Absorptive delays 122
3.5.4 Waveguide reverberators 123
3.5.5 Lossless prototype structures 125
3.5.6 Implementation of absorptive and correction filters 128
3.5.7 Multirate algorithms 128
3.5.8 Time-varying algorithms 129
3.6 Conclusions 130
4
Digital Audio Restoration
Simon Godsill, Peter Rayner and Olivier Cappé
4.1 Introduction
4.2 Modelling of audio signals
4.3 Click Removal
4.3.1 Modelling of clicks
4.3.2 Detection
4.3.3 Replacement of corrupted samples
4.3.4 Statistical methods for the treatment of clicks
4.4 Correlated Noise Pulse Removal
4.5 Background noise reduction
4.5.1 Background noise reduction by short-time spectral attenuation 164
4.5.2 Discussion 177
4.6 Pitch variation defects 177
4.6.1 Frequency domain estimation 179
4.7 Reduction of Non-linear Amplitude Distortion 182
4.7.1 Distortion Modelling 183
4.7.2 Non-linear Signal Models 184
4.7.3 Application of Non-linear models to Distortion Reduction 186
4.7.4 Parameter Estimation 188
4.7.5 Examples 190
4.7.6 Discussion 190
4.8 Other areas 192
4.9 Conclusion and Future Trends 193
Contents vii

viii APPLICATIONS OF DSP TO AUDIO AND ACOUSTICS
5.3.4 Processors
5.4 Conclusion
6
Signal Processing for Hearing Aids
James M. Kates
6.1 Introduction
6.2 Hearing and Hearing Loss
6.2.1 Outer and Middle Ear
6.3 Inner Ear
6.3.1 Retrocochlear and Central Losses
6.3.2 Summary
6.4 Linear Amplification
6.4.1 System Description
6.4.2 Dynamic Range
6.4.3 Distortion
6.4.4 Bandwidth
6.5 Feedback Cancellation
6.6 Compression Amplification
6.6.1 Single-Channel Compression
6.6.2 Two-Channel Compression
6.6.3 Multi-Channel Compression
6.7 Single-Microphone Noise Suppression
6.7.Adaptive Analog Filters
6.7.2 Spectral Subtraction
6.7.3 Spectral Enhancement
6.8 Multi-Microphone Noise Suppression
6.8.1 Directional Microphone Elements
6.8.2 Two-Microphone Adaptive Noise Cancellation
6.8.3 Arrays with Time-Invariant Weights
6.8.4 Two-Microphone Adaptive Arrays
6.8.5 Multi-Microphone Adaptive Arrays
6.8.6 Performance Comparison in a Real Room
6.9 Cochlear Implants
6.10 Conclusions
7
Time and Pitch scale modification of audio signals
Jean Laroche
7.1 Introduction
7.2 Notations and definitions
7.2.1 An underlying sinusoidal model for signals
7.2.2 A definition of time-scale and pitch-scale modification
7.3 Frequency-domain techniques
7.3.1 Methods based on the short-time Fourier transform
7.3.2 Methods based on a signal model
7.4 Time-domain techniques
Contents ix
7.4.1 Principle
7.4.2 Pitch independent methods
7.4.3 Periodicity-driven methods
7.5 Formant modification
7.5.1 Time-domain techniques
7.5.2 Frequency-domain techniques
7.6 Discussion
7.6.1 Generic problems associated with time or pitch scaling
7.6.2 Time-domain vs frequency-domain techniques
8
Wavetable Sampling Synthesis
Dana C. Massie
8.1 Background and introduction
8.1.1 Transition to Digital
8.1.2 Flourishing of Digital Synthesis Methods
8.1.3 Metrics: The Sampling - Synthesis Continuum
8.1.4 Sampling vs. Synthesis
8.2 Wavetable Sampling Synthesis
8.2.1 Playback of digitized musical instrument events.
8.2.2 Entire note - not single period
8.2.3 Pitch Shifting Technologies
8.2.4 Looping of sustain
8.2.5 Multi-sampling
8.2.6 Enveloping
8.2.7 Filtering
8.2.8 Amplitude variations as a function of velocity
8.2.9 Mixing or summation of channels
8.2.10 Multiplexed wavetables
8.3 Conclusion
9
Audio Signal Processing Based on Sinusoidal Analysis/Synthesis
T.F. Quatieri and R. J. McAulay
9.1 Introduction
9.2 Filter Bank Analysis/Synthesis
9.2.1 Additive Synthesis
9.2.2 Phase Vocoder
9.2.3 Motivation for a Sine-Wave Analysis/Synthesis
9.3 Sinusoidal-Based Analysis/Synthesis
9.3.1 Model
9.3.2 Estimation of Model Parameters
9.3.3 Frame-to-Frame Peak Matching
9.3.4 Synthesis
9.3.5 Experimental Results
9.3.6 Applications of the Baseline System
9.3.7 Time-Frequency Resolution
9.4 Source/Filter Phase Model
x APPLICATIONS OF DSP TO AUDIO AND ACOUSTICS
9.4.1 Model 367
9.4.2 Phase Coherence in Signal Modification 368
9.4.3 Revisiting the Filter Bank-Based Approach 381
9.5 Additive Deterministic/Stochastic Model 384
9.5.1 Model 385
9.5.2 Analysis/Synthesis 387
9.5.3 Applications 390
9.6 Signal Separation Using a Two-Voice Model 392
9.6.1 Formulation of the Separation Problem 392
9.6.2 Analysis and Separation 396
9.6.3 The Ambiguity Problem 399
9.6.4 Pitch and Voicing Estimation 402
9.7 FM Synthesis 403
9.7.1 Principles 404
9.7.2 Representation of Musical Sound 407
9.7.3 Parameter Estimation 409
9.7.4 Extensions 411
9.8 Conclusions 411
10
Principles of Digital Waveguide Models of Musical Instruments 417
Julius O. Smith III
10.1 Introduction 418
10.1.1 Antecedents in Speech Modeling 418
10.1.2 Physical Models in Music Synthesis 420
10.1.3 Summary 422
10.2 The Ideal Vibrating String 423
10.2.1 The Finite Difference Approximation 424
10.2.2 Traveling-Wave Solution 426
10.3 Sampling the Traveling Waves 426
10.3.1 Relation to Finite Difference Recursion 430
10.4 Alternative Wave Variables 431
10.4.1 Spatial Derivatives 431
10.4.2 Force Waves 432
10.4.3 Power Waves 434
10.4.4 Energy Density Waves 435
10.4.5 Root-Power Waves 436
10.5 Scattering at an Impedance Discontinuity 436
10.5.1 The Kelly-Lochbaum and One-Multiply Scattering Junctions 439
10.5.2 Normalized Scattering Junctions 441
10.5.3 Junction Passivity 443
10.6 Scattering at a Loaded Junction of N Waveguides 446
10.7 The Lossy One-Dimensional Wave Equation 448
10.7.1 Loss Consolidation 450
10.7.2 Frequency-Dependent Losses 451
10.8 The Dispersive One-Dimensional Wave Equation 451
10.9 Single-Reed Instruments 455
Contents xi
10.9.1 Clarinet Overview 457
10.9.2 Single-Reed Theory 458
10.10 Bowed Strings 462
10.10.1 Violin Overview 463
10.10.2 The Bow-String Scattering Junction 464
10.11 Conclusions 466
References 467
Index 535
List of Figures
Basic philosophy used in perceptual audio quality determination
Excitation pattern for a single sinusoidal tone
Excitation pattern for a single click
Excitation pattern for a short tone burst
Masking model overview
Time-domain smearing as a function of frequency
Basic auditory transformations used in the PAQM
Relation between MOS and PAQM, ISO/MPEG 1990 database
Relation between MOS and PAQM, ISO/MPEG 1991 database
Relation between MOS and PAQM, ITU-R 1993 database
Relation between MOS and PAQM, ETSI GSM full rate database
Relation between MOS and PAQM, ETSI GSM half rate database
Basic approach used in the development of PAQMC
Relation between MOS and PAQMC , ISO/MPEG 1991 database
Relation between MOS and PAQMC , ITU-R 1993 database
Relation between MOS and PAQMC , ETSI GSM full rate database
Relation between MOS and PAQMC , ETSI GSM half rate database
Relation between MOS and PSQM, ETSI GSM full rate database
Relation between MOS and PSQM, ETSI GSM half rate database
Relation between MOS and PSQM, ITU-T German speech

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